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Journal Articles
- 2024
- [j19]Kaiyang Zhou, Ziwei Liu, Xiaohua Zhai, Chunyuan Li, Kate Saenko:
Guest Editorial: Special Issue on the Promises and Dangers of Large Vision Models. Int. J. Comput. Vis. 132(4): 1009-1011 (2024) - [j18]Ping Hu, Simon Niklaus, Lu Zhang, Stan Sclaroff, Kate Saenko:
Video Frame Interpolation With Many-to-Many Splatting and Spatial Selective Refinement. IEEE Trans. Pattern Anal. Mach. Intell. 46(2): 823-836 (2024) - [j17]Ping Hu, Ximeng Sun, Stan Sclaroff, Kate Saenko:
DualCoOp++: Fast and Effective Adaptation to Multi-Label Recognition With Limited Annotations. IEEE Trans. Pattern Anal. Mach. Intell. 46(5): 3450-3462 (2024) - 2022
- [j16]Shoumik Sovan Majumdar, Shubhangi Jain, Isidora Chara Tourni, Arsenii Mustafin, Diala Lteif, Stan Sclaroff, Kate Saenko, Sarah Adel Bargal:
Ani-GIFs: A benchmark dataset for domain generalization of action recognition from GIFs. Frontiers Comput. Sci. 4 (2022) - [j15]Bryan A. Plummer, Kevin J. Shih, Yichen Li, Ke Xu, Svetlana Lazebnik, Stan Sclaroff, Kate Saenko:
Revisiting Image-Language Networks for Open-Ended Phrase Detection. IEEE Trans. Pattern Anal. Mach. Intell. 44(4): 2155-2167 (2022) - [j14]Ping Hu, Stan Sclaroff, Kate Saenko:
Leveraging Geometric Structure for Label-Efficient Semi-Supervised Scene Segmentation. IEEE Trans. Image Process. 31: 6320-6330 (2022) - 2021
- [j13]Sarah Adel Bargal, Andrea Zunino, Vitali Petsiuk, Jianming Zhang, Kate Saenko, Vittorio Murino, Stan Sclaroff:
Guided Zoom: Zooming into Network Evidence to Refine Fine-Grained Model Decisions. IEEE Trans. Pattern Anal. Mach. Intell. 43(11): 4196-4202 (2021) - [j12]Ping Hu, Federico Perazzi, Fabian Caba Heilbron, Oliver Wang, Zhe Lin, Kate Saenko, Stan Sclaroff:
Real-Time Semantic Segmentation With Fast Attention. IEEE Robotics Autom. Lett. 6(1): 263-270 (2021) - [j11]Siddharth Mysore, Bassel Mabsout, Kate Saenko, Renato Mancuso:
How to Train Your Quadrotor: A Framework for Consistently Smooth and Responsive Flight Control via Reinforcement Learning. ACM Trans. Cyber Phys. Syst. 5(4): 36:1-36:24 (2021) - 2019
- [j10]Huijuan Xu, Abir Das, Kate Saenko:
Two-Stream Region Convolutional 3D Network for Temporal Activity Detection. IEEE Trans. Pattern Anal. Mach. Intell. 41(10): 2319-2332 (2019) - 2018
- [j9]Marie-Francine Moens, Katerina Pastra, Kate Saenko, Tinne Tuytelaars:
Vision and Language Integration Meets Multimedia Fusion. IEEE Multim. 25(2): 7-10 (2018) - 2017
- [j8]Margaret Mitchell, John C. Platt, Kate Saenko:
Guest Editorial: Image and Language Understanding. Int. J. Comput. Vis. 123(1): 1-3 (2017) - [j7]Andreas ten Pas, Marcus Gualtieri, Kate Saenko, Robert Platt Jr.:
Grasp Pose Detection in Point Clouds. Int. J. Robotics Res. 36(13-14): 1455-1473 (2017) - [j6]Jeff Donahue, Lisa Anne Hendricks, Marcus Rohrbach, Subhashini Venugopalan, Sergio Guadarrama, Kate Saenko, Trevor Darrell:
Long-Term Recurrent Convolutional Networks for Visual Recognition and Description. IEEE Trans. Pattern Anal. Mach. Intell. 39(4): 677-691 (2017) - 2016
- [j5]Sergio Guadarrama, Erik Rodner, Kate Saenko, Trevor Darrell:
Understanding object descriptions in robotics by open-vocabulary object retrieval and detection. Int. J. Robotics Res. 35(1-3): 265-280 (2016) - [j4]Judy Hoffman, Deepak Pathak, Eric Tzeng, Jonathan Long, Sergio Guadarrama, Trevor Darrell, Kate Saenko:
Large Scale Visual Recognition through Adaptation using Joint Representation and Multiple Instance Learning. J. Mach. Learn. Res. 17: 142:1-142:31 (2016) - 2014
- [j3]Judy Hoffman, Erik Rodner, Jeff Donahue, Brian Kulis, Kate Saenko:
Asymmetric and Category Invariant Feature Transformations for Domain Adaptation. Int. J. Comput. Vis. 109(1-2): 28-41 (2014) - [j2]Ayan Chakrabarti, Ying Xiong, Baochen Sun, Trevor Darrell, Daniel Scharstein, Todd E. Zickler, Kate Saenko:
Modeling Radiometric Uncertainty for Vision with Tone-Mapped Color Images. IEEE Trans. Pattern Anal. Mach. Intell. 36(11): 2185-2198 (2014) - 2009
- [j1]Kate Saenko, Karen Livescu, James R. Glass, Trevor Darrell:
Multistream Articulatory Feature-Based Models for Visual Speech Recognition. IEEE Trans. Pattern Anal. Mach. Intell. 31(9): 1700-1707 (2009)
Conference and Workshop Papers
- 2024
- [c171]Andrea Burns, Kate Saenko, Bryan A. Plummer:
Tell Me What's Next: Textual Foresight for Generic UI Representations. ACL (Findings) 2024: 4590-4611 - [c170]Reuben Tan, Ximeng Sun, Ping Hu, Jui-Hsien Wang, Hanieh Deilamsalehy, Bryan A. Plummer, Bryan Russell, Kate Saenko:
Koala: Key Frame-Conditioned Long Video-LLM. CVPR 2024: 13581-13591 - [c169]Ximeng Sun, Rameswar Panda, Chun-Fu Richard Chen, Naigang Wang, Bowen Pan, Aude Oliva, Rogério Feris, Kate Saenko:
Improved Techniques for Quantizing Deep Networks with Adaptive Bit-Widths. WACV 2024: 946-956 - [c168]Piotr Teterwak, Soren Nelson, Nikoli Dryden, Dina Bashkirova, Kate Saenko, Bryan A. Plummer:
Learning to Compose SuperWeights for Neural Parameter Allocation Search. WACV 2024: 2739-2748 - 2023
- [c167]Dina Bashkirova, José Lezama, Kihyuk Sohn, Kate Saenko, Irfan Essa:
MaskSketch: Unpaired Structure-guided Masked Image Generation. CVPR 2023: 1879-1889 - [c166]Kuniaki Saito, Kihyuk Sohn, Xiang Zhang, Chun-Liang Li, Chen-Yu Lee, Kate Saenko, Tomas Pfister:
Prefix Conditioning Unifies Language and Label Supervision. CVPR 2023: 2861-2870 - [c165]Reuben Tan, Arijit Ray, Andrea Burns, Bryan A. Plummer, Justin Salamon, Oriol Nieto, Bryan Russell, Kate Saenko:
Language-Guided Audio-Visual Source Separation via Trimodal Consistency. CVPR 2023: 10575-10584 - [c164]Kuniaki Saito, Kihyuk Sohn, Xiang Zhang, Chun-Liang Li, Chen-Yu Lee, Kate Saenko, Tomas Pfister:
Pic2Word: Mapping Pictures to Words for Zero-shot Composed Image Retrieval. CVPR 2023: 19305-19314 - [c163]Maan Qraitem, Kate Saenko, Bryan A. Plummer:
Bias Mimicking: A Simple Sampling Approach for Bias Mitigation. CVPR 2023: 20311-20320 - [c162]Andrea Burns, Krishna Srinivasan, Joshua Ainslie, Geoff Brown, Bryan A. Plummer, Kate Saenko, Jianmo Ni, Mandy Guo:
A Suite of Generative Tasks for Multi-Level Multimodal Webpage Understanding. EMNLP 2023: 1917-1947 - [c161]Ximeng Sun, Pengchuan Zhang, Peizhao Zhang, Hardik Shah, Kate Saenko, Xide Xia:
DIME-FM : DIstilling Multimodal and Efficient Foundation Models. ICCV 2023: 15475-15487 - [c160]Arijit Ray, Filip Radenovic, Abhimanyu Dubey, Bryan A. Plummer, Ranjay Krishna, Kate Saenko:
Cola: A Benchmark for Compositional Text-to-image Retrieval. NeurIPS 2023 - [c159]Ben Usman, Dina Bashkirova, Kate Saenko:
RIFT: Disentangled Unsupervised Image Translation via Restricted Information Flow. WACV 2023: 2419-2428 - [c158]Aadarsh Sahoo, Rameswar Panda, Rogério Feris, Kate Saenko, Abir Das:
Select, Label, and Mix: Learning Discriminative Invariant Feature Representations for Partial Domain Adaptation. WACV 2023: 4199-4208 - 2022
- [c157]Ping Hu, Simon Niklaus, Stan Sclaroff, Kate Saenko:
Many-to-many Splatting for Efficient Video Frame Interpolation. CVPR 2022: 3543-3552 - [c156]Sivan Harary, Eli Schwartz, Assaf Arbelle, Peter W. J. Staar, Shady Abu-Hussein, Elad Amrani, Roei Herzig, Amit Alfassy, Raja Giryes, Hilde Kuehne, Dina Katabi, Kate Saenko, Rogério Feris, Leonid Karlinsky:
Unsupervised Domain Generalization by Learning a Bridge Across Domains. CVPR 2022: 5270-5280 - [c155]Ben Usman, Andrea Tagliasacchi, Kate Saenko, Avneesh Sud:
MetaPose: Fast 3D Pose from Multiple Views without 3D Supervision. CVPR 2022: 6749-6760 - [c154]Samarth Mishra, Rameswar Panda, Cheng Perng Phoo, Chun-Fu Richard Chen, Leonid Karlinsky, Kate Saenko, Venkatesh Saligrama, Rogério Schmidt Feris:
Task2Sim: Towards Effective Pre-training and Transfer from Synthetic Data. CVPR 2022: 9184-9194 - [c153]Dina Bashkirova, Mohamed Abdelfattah, Ziliang Zhu, James Akl, Fadi M. Alladkani, Ping Hu, Vitaly Ablavsky, Berk Çalli, Sarah Adel Bargal, Kate Saenko:
ZeroWaste Dataset: Towards Deformable Object Segmentation in Cluttered Scenes. CVPR 2022: 21115-21125 - [c152]Kuniaki Saito, Ping Hu, Trevor Darrell, Kate Saenko:
Learning to Detect Every Thing in an Open World. ECCV (24) 2022: 268-284 - [c151]Andrea Burns, Deniz Arsan, Sanjna Agrawal, Ranjitha Kumar, Kate Saenko, Bryan A. Plummer:
A Dataset for Interactive Vision-Language Navigation with Unknown Command Feasibility. ECCV (8) 2022: 312-328 - [c150]Jack Hessel, Jena D. Hwang, Jae Sung Park, Rowan Zellers, Chandra Bhagavatula, Anna Rohrbach, Kate Saenko, Yejin Choi:
The Abduction of Sherlock Holmes: A Dataset for Visual Abductive Reasoning. ECCV (36) 2022: 558-575 - [c149]Donghyun Kim, Kaihong Wang, Kate Saenko, Margrit Betke, Stan Sclaroff:
A Unified Framework for Domain Adaptive Pose Estimation. ECCV (33) 2022: 603-620 - [c148]Donghyun Kim, Kaihong Wang, Stan Sclaroff, Kate Saenko:
A Broad Study of Pre-training for Domain Generalization and Adaptation. ECCV (33) 2022: 621-638 - [c147]Reuben Tan, Bryan A. Plummer, Kate Saenko, J. P. Lewis, Avneesh Sud, Thomas Leung:
NewsStories: Illustrating Articles with Visual Summaries. ECCV (36) 2022: 644-661 - [c146]Siddharth Mysore, George Cheng, Yunqi Zhao, Kate Saenko, Meng Wu:
Multi-Critic Actor Learning: Teaching RL Policies to Act with Style. ICLR 2022 - [c145]Bryan A. Plummer, Nikoli Dryden, Julius Frost, Torsten Hoefler, Kate Saenko:
Neural Parameter Allocation Search. ICLR 2022 - [c144]Shiori Sagawa, Pang Wei Koh, Tony Lee, Irena Gao, Sang Michael Xie, Kendrick Shen, Ananya Kumar, Weihua Hu, Michihiro Yasunaga, Henrik Marklund, Sara Beery, Etienne David, Ian Stavness, Wei Guo, Jure Leskovec, Kate Saenko, Tatsunori Hashimoto, Sergey Levine, Chelsea Finn, Percy Liang:
Extending the WILDS Benchmark for Unsupervised Adaptation. ICLR 2022 - [c143]Amit Alfassy, Assaf Arbelle, Oshri Halimi, Sivan Harary, Roei Herzig, Eli Schwartz, Rameswar Panda, Michele Dolfi, Christoph Auer, Peter W. J. Staar, Kate Saenko, Rogério Feris, Leonid Karlinsky:
FETA: Towards Specializing Foundational Models for Expert Task Applications. NeurIPS 2022 - [c142]Yo-whan Kim, Samarth Mishra, SouYoung Jin, Rameswar Panda, Hilde Kuehne, Leonid Karlinsky, Venkatesh Saligrama, Kate Saenko, Aude Oliva, Rogério Feris:
How Transferable are Video Representations Based on Synthetic Data? NeurIPS 2022 - [c141]Nataniel Ruiz, Sarah A. Bargal, Cihang Xie, Kate Saenko, Stan Sclaroff:
Finding Differences Between Transformers and ConvNets Using Counterfactual Simulation Testing. NeurIPS 2022 - [c140]Ximeng Sun, Ping Hu, Kate Saenko:
DualCoOp: Fast Adaptation to Multi-Label Recognition with Limited Annotations. NeurIPS 2022 - [c139]Dina Bashkirova, Ben Usman, Kate Saenko:
Evaluation of Correctness in Unsupervised Many-to-Many Image Translation. WACV 2022: 1-10 - 2021
- [c138]Samarth Mishra, Kate Saenko, Venkatesh Saligrama:
Surprisingly Simple Semi-Supervised Domain Adaptation with Pretraining and Consistency. BMVC 2021: 177 - [c137]Siddharth Mysore, Bassel El Mabsout, Renato Mancuso, Kate Saenko:
Honey. I Shrunk The Actor: A Case Study on Preserving Performance with Smaller Actors in Actor-Critic RL. CoG 2021: 1-8 - [c136]Andrea Zunino, Sarah Adel Bargal, Riccardo Volpi, Mehrnoosh Sameki, Jianming Zhang, Stan Sclaroff, Vittorio Murino, Kate Saenko:
Explainable Deep Classification Models for Domain Generalization. CVPR Workshops 2021: 3233-3242 - [c135]Spencer Whitehead, Hui Wu, Heng Ji, Rogério Feris, Kate Saenko:
Separating Skills and Concepts for Novel Visual Question Answering. CVPR 2021: 5632-5641 - [c134]Guy Bukchin, Eli Schwartz, Kate Saenko, Ori Shahar, Rogério Feris, Raja Giryes, Leonid Karlinsky:
Fine-Grained Angular Contrastive Learning With Coarse Labels. CVPR 2021: 8730-8740 - [c133]Ankit Singh, Omprakash Chakraborty, Ashutosh Varshney, Rameswar Panda, Rogério Feris, Kate Saenko, Abir Das:
Semi-Supervised Action Recognition With Temporal Contrastive Learning. CVPR 2021: 10389-10399 - [c132]Vitali Petsiuk, Rajiv Jain, Varun Manjunatha, Vlad I. Morariu, Ashutosh Mehra, Vicente Ordonez, Kate Saenko:
Black-Box Explanation of Object Detectors via Saliency Maps. CVPR 2021: 11443-11452 - [c131]Assaf Arbelle, Sivan Doveh, Amit Alfassy, Joseph Shtok, Guy Lev, Eli Schwartz, Hilde Kuehne, Hila Barak Levi, Prasanna Sattigeri, Rameswar Panda, Chun-Fu Chen, Alex M. Bronstein, Kate Saenko, Shimon Ullman, Raja Giryes, Rogério Feris, Leonid Karlinsky:
Detector-Free Weakly Supervised Grounding by Separation. ICCV 2021: 1781-1792 - [c130]Ximeng Sun, Rameswar Panda, Chun-Fu (Richard) Chen, Aude Oliva, Rogério Feris, Kate Saenko:
Dynamic Network Quantization for Efficient Video Inference. ICCV 2021: 7355-7365 - [c129]Rameswar Panda, Chun-Fu (Richard) Chen, Quanfu Fan, Ximeng Sun, Kate Saenko, Aude Oliva, Rogério Feris:
AdaMML: Adaptive Multi-Modal Learning for Efficient Video Recognition. ICCV 2021: 7556-7565 - [c128]Baifeng Shi, Qi Dai, Judy Hoffman, Kate Saenko, Trevor Darrell, Huijuan Xu:
Temporal Action Detection with Multi-level Supervision. ICCV 2021: 8002-8012 - [c127]Viraj Prabhu, Arjun Chandrasekaran, Kate Saenko, Judy Hoffman:
Active Domain Adaptation via Clustering Uncertainty-weighted Embeddings. ICCV 2021: 8485-8494 - [c126]Kuniaki Saito, Kate Saenko:
OVANet: One-vs-All Network for Universal Domain Adaptation. ICCV 2021: 8980-8989 - [c125]Donghyun Kim, Kuniaki Saito, Tae-Hyun Oh, Bryan A. Plummer, Stan Sclaroff, Kate Saenko:
CDS: Cross-Domain Self-supervised Pre-training. ICCV 2021: 9103-9112 - [c124]Kuniaki Saito, Donghyun Kim, Piotr Teterwak, Stan Sclaroff, Trevor Darrell, Kate Saenko:
Tune it the Right Way: Unsupervised Validation of Domain Adaptation via Soft Neighborhood Density. ICCV 2021: 9164-9173 - [c123]Donghyun Kim, Yi-Hsuan Tsai, Bingbing Zhuang, Xiang Yu, Stan Sclaroff, Kate Saenko, Manmohan Chandraker:
Learning Cross-Modal Contrastive Features for Video Domain Adaptation. ICCV 2021: 13598-13607 - [c122]Donghyun Kim, Kuniaki Saito, Samarth Mishra, Stan Sclaroff, Kate Saenko, Bryan A. Plummer:
Self-supervised Visual Attribute Learning for Fashion Compatibility. ICCVW 2021: 1057-1066 - [c121]Yue Meng, Rameswar Panda, Chung-Ching Lin, Prasanna Sattigeri, Leonid Karlinsky, Kate Saenko, Aude Oliva, Rogério Feris:
AdaFuse: Adaptive Temporal Fusion Network for Efficient Action Recognition. ICLR 2021 - [c120]Bowen Pan, Rameswar Panda, Camilo Luciano Fosco, Chung-Ching Lin, Alex J. Andonian, Yue Meng, Kate Saenko, Aude Oliva, Rogério Feris:
VA-RED2: Video Adaptive Redundancy Reduction. ICLR 2021 - [c119]Siddharth Mysore, Bassel Mabsout, Renato Mancuso, Kate Saenko:
Regularizing Action Policies for Smooth Control with Reinforcement Learning. ICRA 2021: 1810-1816 - [c118]Masaki Yamazaki, Xingchao Peng, Kuniaki Saito, Ping Hu, Kate Saenko, Yasuhiro Taniguchi:
Weakly Supervised Domain Adaptation using Super-pixel labeling for Semantic Segmentation. MVA 2021: 1-5 - [c117]Dina Bashkirova, Dan Hendrycks, Donghyun Kim, Haojin Liao, Samarth Mishra, Chandramouli Rajagopalan, Kate Saenko, Kuniaki Saito, Burhan Ul Tayyab, Piotr Teterwak, Ben Usman:
VisDA-2021 Competition: Universal Domain Adaptation to Improve Performance on Out-of-Distribution Data. NeurIPS (Competition and Demos) 2021: 66-79 - [c116]Dina Bashkirova, Samarth Mishra, Diala Lteif, Piotr Teterwak, Donghyun Kim, Fadi M. Alladkani, James Akl, Berk Çalli, Sarah Adel Bargal, Kate Saenko, Daehan Kim, Minseok Seo, YoungJin Jeon, Dong-Geol Choi, Shahaf Ettedgui, Raja Giryes, Shady Abu-Hussein, Binhui Xie, Shuang Li:
VisDA 2022 Challenge: Domain Adaptation for Industrial Waste Sorting. NeurIPS (Competition and Demos) 2021: 104-118 - [c115]Reuben Tan, Bryan A. Plummer, Kate Saenko, Hailin Jin, Bryan Russell:
Look at What I'm Doing: Self-Supervised Spatial Grounding of Narrations in Instructional Videos. NeurIPS 2021: 14476-14487 - [c114]Aadarsh Sahoo, Rutav Shah, Rameswar Panda, Kate Saenko, Abir Das:
Contrast and Mix: Temporal Contrastive Video Domain Adaptation with Background Mixing. NeurIPS 2021: 23386-23400 - [c113]Kuniaki Saito, Donghyun Kim, Kate Saenko:
OpenMatch: Open-Set Semi-supervised Learning with Open-set Consistency Regularization. NeurIPS 2021: 25956-25967 - [c112]Reuben Tan, Huijuan Xu, Kate Saenko, Bryan A. Plummer:
LoGAN: Latent Graph Co-Attention Network for Weakly-Supervised Video Moment Retrieval. WACV 2021: 2082-2091 - 2020
- [c111]Donghyun Kim, Kuniaki Saito, Kate Saenko, Stan Sclaroff, Bryan A. Plummer:
MULE: Multimodal Universal Language Embedding. AAAI 2020: 11254-11261 - [c110]Yue Meng, Chung-Ching Lin, Rameswar Panda, Prasanna Sattigeri, Leonid Karlinsky, Aude Oliva, Kate Saenko, Rogério Feris:
AR-Net: Adaptive Frame Resolution for Efficient Action Recognition. ECCV (7) 2020: 86-104 - [c109]Yunhui Guo, Noel Codella, Leonid Karlinsky, James V. Codella, John R. Smith, Kate Saenko, Tajana Rosing, Rogério Feris:
A Broader Study of Cross-Domain Few-Shot Learning. ECCV (27) 2020: 124-141 - [c108]Andrea Burns, Donghyun Kim, Derry Wijaya, Kate Saenko, Bryan A. Plummer:
Learning to Scale Multilingual Representations for Vision-Language Tasks. ECCV (4) 2020: 197-213 - [c107]Kuniaki Saito, Kate Saenko, Ming-Yu Liu:
COCO-FUNIT: Few-Shot Unsupervised Image Translation with a Content Conditioned Style Encoder. ECCV (3) 2020: 382-398 - [c106]Shuhan Tan, Xingchao Peng, Kate Saenko:
Class-Imbalanced Domain Adaptation: An Empirical Odyssey. ECCV Workshops (1) 2020: 585-602 - [c105]Bryan A. Plummer, Mariya I. Vasileva, Vitali Petsiuk, Kate Saenko, David A. Forsyth:
Why Do These Match? Explaining the Behavior of Image Similarity Models. ECCV (11) 2020: 652-669 - [c104]Xingchao Peng, Yichen Li, Kate Saenko:
Domain2Vec: Domain Embedding for Unsupervised Domain Adaptation. ECCV (6) 2020: 756-774 - [c103]Reuben Tan, Bryan A. Plummer, Kate Saenko:
Detecting Cross-Modal Inconsistency to Defend Against Neural Fake News. EMNLP (1) 2020: 2081-2106 - [c102]Xingchao Peng, Zijun Huang, Yizhe Zhu, Kate Saenko:
Federated Adversarial Domain Adaptation. ICLR 2020 - [c101]Sarah Adel Bargal, Andrea Zunino, Vitali Petsiuk, Jianming Zhang, Vittorio Murino, Stan Sclaroff, Kate Saenko:
Beyond the Visual Analysis of Deep Model Saliency. xxAI@ICML 2020: 255-269 - [c100]Ulrich Viereck, Kate Saenko, Robert Platt Jr.:
Learning Visual Servo Policies via Planner Cloning. ISER 2020: 285-295 - [c99]Ping Hu, Stan Sclaroff, Kate Saenko:
Uncertainty-Aware Learning for Zero-Shot Semantic Segmentation. NeurIPS 2020 - [c98]Kuniaki Saito, Donghyun Kim, Stan Sclaroff, Kate Saenko:
Universal Domain Adaptation through Self Supervision. NeurIPS 2020 - [c97]Baifeng Shi, Judy Hoffman, Kate Saenko, Trevor Darrell, Huijuan Xu:
Auxiliary Task Reweighting for Minimum-data Learning. NeurIPS 2020 - [c96]Ximeng Sun, Rameswar Panda, Rogério Feris, Kate Saenko:
AdaShare: Learning What To Share For Efficient Deep Multi-Task Learning. NeurIPS 2020 - [c95]Ben Usman, Avneesh Sud, Nick Dufour, Kate Saenko:
Log-Likelihood Ratio Minimizing Flows: Towards Robust and Quantifiable Neural Distribution Alignment. NeurIPS 2020 - [c94]Ping Hu, Jun Liu, Gang Wang, Vitaly Ablavsky, Kate Saenko, Stan Sclaroff:
DIPNet: Dynamic Identity Propagation Network for Video Object Segmentation. WACV 2020: 1893-1902 - [c93]Ximeng Sun, Huijuan Xu, Kate Saenko:
TwoStreamVAN: Improving Motion Modeling in Video Generation. WACV 2020: 2733-2742 - 2019
- [c92]Huijuan Xu, Kun He, Bryan A. Plummer, Leonid Sigal, Stan Sclaroff, Kate Saenko:
Multilevel Language and Vision Integration for Text-to-Clip Retrieval. AAAI 2019: 9062-9069 - [c91]Ronghang Hu, Daniel Fried, Anna Rohrbach, Dan Klein, Trevor Darrell, Kate Saenko:
Are You Looking? Grounding to Multiple Modalities in Vision-and-Language Navigation. ACL (1) 2019: 6551-6557 - [c90]Sarah Adel Bargal, Andrea Zunino, Vitali Petsiuk, Jianming Zhang, Kate Saenko, Vittorio Murino, Stan Sclaroff:
Guided Zoom: Questioning Network Evidence for Fine-grained Classification. BMVC 2019: 17 - [c89]Sarah Adel Bargal, Andrea Zunino, Vitali Petsiuk, Jianming Zhang, Kate Saenko, Vittorio Murino, Stan Sclaroff:
Are CNN Predictions based on Reasonable Evidence? CVPR Workshops 2019: 67-70 - [c88]Kuniaki Saito, Yoshitaka Ushiku, Tatsuya Harada, Kate Saenko:
Strong-Weak Distribution Alignment for Adaptive Object Detection. CVPR 2019: 6956-6965 - [c87]Xingchao Peng, Qinxun Bai, Xide Xia, Zijun Huang, Kate Saenko, Bo Wang:
Moment Matching for Multi-Source Domain Adaptation. ICCV 2019: 1406-1415 - [c86]Andrea Burns, Reuben Tan, Kate Saenko, Stan Sclaroff, Bryan A. Plummer:
Language Features Matter: Effective Language Representations for Vision-Language Tasks. ICCV 2019: 7473-7482 - [c85]Kuniaki Saito, Donghyun Kim, Stan Sclaroff, Trevor Darrell, Kate Saenko:
Semi-Supervised Domain Adaptation via Minimax Entropy. ICCV 2019: 8049-8057 - [c84]Ben Usman, Nick Dufour, Kate Saenko, Chris Bregler:
PuppetGAN: Cross-Domain Image Manipulation by Demonstration. ICCV 2019: 9449-9457 - [c83]Ronghang Hu, Anna Rohrbach, Trevor Darrell, Kate Saenko:
Language-Conditioned Graph Networks for Relational Reasoning. ICCV 2019: 10293-10302 - [c82]Reuben Tan, Mariya I. Vasileva, Kate Saenko, Bryan A. Plummer:
Learning Similarity Conditions Without Explicit Supervision. ICCV 2019: 10372-10381 - [c81]Andrew Levy, George Dimitri Konidaris, Robert Platt Jr., Kate Saenko:
Learning Multi-Level Hierarchies with Hindsight. ICLR (Poster) 2019 - [c80]Xingchao Peng, Zijun Huang, Ximeng Sun, Kate Saenko:
Domain Agnostic Learning with Disentangled Representations. ICML 2019: 5102-5112 - [c79]Dina Bashkirova, Ben Usman, Kate Saenko:
Adversarial Self-Defense for Cycle-Consistent GANs. NeurIPS 2019: 635-645 - [c78]Huijuan Xu, Boyang Li, Vasili Ramanishka, Leonid Sigal, Kate Saenko:
Joint Event Detection and Description in Continuous Video Streams. WACV Workshops 2019: 25-26 - [c77]Huijuan Xu, Boyang Li, Vasili Ramanishka, Leonid Sigal, Kate Saenko:
Joint Event Detection and Description in Continuous Video Streams. WACV 2019: 396-405 - 2018
- [c76]Vitali Petsiuk, Abir Das, Kate Saenko:
RISE: Randomized Input Sampling for Explanation of Black-box Models. BMVC 2018: 151 - [c75]Xingchao Peng, Ben Usman, Neela Kaushik, Dequan Wang, Judy Hoffman, Kate Saenko:
VisDA: A Synthetic-to-Real Benchmark for Visual Domain Adaptation. CVPR Workshops 2018: 2021-2026 - [c74]Vasili Ramanishka, Yi-Ting Chen, Teruhisa Misu, Kate Saenko:
Toward Driving Scene Understanding: A Dataset for Learning Driver Behavior and Causal Reasoning. CVPR 2018: 7699-7707 - [c73]Ronghang Hu, Jacob Andreas, Trevor Darrell, Kate Saenko:
Explainable Neural Computation via Stack Neural Module Networks. ECCV (7) 2018: 55-71 - [c72]Lisa Anne Hendricks, Kaylee Burns, Kate Saenko, Trevor Darrell, Anna Rohrbach:
Women Also Snowboard: Overcoming Bias in Captioning Models. ECCV (3) 2018: 793-811 - [c71]Anna Rohrbach, Lisa Anne Hendricks, Kaylee Burns, Trevor Darrell, Kate Saenko:
Object Hallucination in Image Captioning. EMNLP 2018: 4035-4045 - [c70]Kuniaki Saito, Yoshitaka Ushiku, Tatsuya Harada, Kate Saenko:
Adversarial Dropout Regularization. ICLR (Poster) 2018 - [c69]Ben Usman, Kate Saenko, Brian Kulis:
Stable Distribution Alignment Using the Dual of the Adversarial Distance. ICLR (Workshop) 2018 - [c68]Judy Hoffman, Eric Tzeng, Taesung Park, Jun-Yan Zhu, Phillip Isola, Kate Saenko, Alexei A. Efros, Trevor Darrell:
CyCADA: Cycle-Consistent Adversarial Domain Adaptation. ICML 2018: 1994-2003 - [c67]Ulrich Viereck, Xingchao Peng, Kate Saenko, Robert Platt Jr.:
Adapting Control Policies from Simulation to Reality Using a Pairwise Loss. ISER 2018: 256-266 - [c66]Daniel Fried, Ronghang Hu, Volkan Cirik, Anna Rohrbach, Jacob Andreas, Louis-Philippe Morency, Taylor Berg-Kirkpatrick, Kate Saenko, Dan Klein, Trevor Darrell:
Speaker-Follower Models for Vision-and-Language Navigation. NeurIPS 2018: 3318-3329 - [c65]Xingchao Peng, Kate Saenko:
Synthetic to Real Adaptation with Generative Correlation Alignment Networks. WACV 2018: 1982-1991 - 2017
- [c64]Ulrich Viereck, Andreas ten Pas, Kate Saenko, Robert Platt Jr.:
Learning a visuomotor controller for real world robotic grasping using simulated depth images. CoRL 2017: 291-300 - [c63]Subhashini Venugopalan, Lisa Anne Hendricks, Marcus Rohrbach, Raymond J. Mooney, Trevor Darrell, Kate Saenko:
Captioning Images with Diverse Objects. CVPR 2017: 1170-1178 - [c62]Eric Tzeng, Judy Hoffman, Kate Saenko, Trevor Darrell:
Adversarial Discriminative Domain Adaptation. CVPR 2017: 2962-2971 - [c61]Vasili Ramanishka, Abir Das, Jianming Zhang, Kate Saenko:
Top-Down Visual Saliency Guided by Captions. CVPR 2017: 3135-3144 - [c60]Ronghang Hu, Marcus Rohrbach, Jacob Andreas, Trevor Darrell, Kate Saenko:
Modeling Relationships in Referential Expressions with Compositional Modular Networks. CVPR 2017: 4418-4427 - [c59]Ronghang Hu, Jacob Andreas, Marcus Rohrbach, Trevor Darrell, Kate Saenko:
Learning to Reason: End-to-End Module Networks for Visual Question Answering. ICCV 2017: 804-813 - [c58]Huijuan Xu, Abir Das, Kate Saenko:
R-C3D: Region Convolutional 3D Network for Temporal Activity Detection. ICCV 2017: 5794-5803 - [c57]Baochen Sun, Xingchao Peng, Stella X. Yu, Kate Saenko:
Ground2sky label transfer for fine-grained aerial car recognition. ICIP 2017: 360-364 - [c56]Eric Tzeng, Judy Hoffman, Kate Saenko, Trevor Darrell:
Adversarial Discriminative Domain Adaptation (workshop extended abstract). ICLR (Workshop) 2017 - 2016
- [c55]Baochen Sun, Jiashi Feng, Kate Saenko:
Return of Frustratingly Easy Domain Adaptation. AAAI 2016: 2058-2065 - [c54]Xingchao Peng, Kate Saenko:
Combining Texture and Shape Cues for Object Recognition with Minimal Supervision. ACCV (4) 2016: 256-272 - [c53]William Boag, Renan Campos, Kate Saenko, Anna Rumshisky:
MUTT: Metric Unit TesTing for Language Generation Tasks. ACL (1) 2016 - [c52]Lisa Anne Hendricks, Subhashini Venugopalan, Marcus Rohrbach, Raymond J. Mooney, Kate Saenko, Trevor Darrell:
Deep Compositional Captioning: Describing Novel Object Categories without Paired Training Data. CVPR 2016: 1-10 - [c51]Ronghang Hu, Huazhe Xu, Marcus Rohrbach, Jiashi Feng, Kate Saenko, Trevor Darrell:
Natural Language Object Retrieval. CVPR 2016: 4555-4564 - [c50]Baochen Sun, Kate Saenko:
Deep CORAL: Correlation Alignment for Deep Domain Adaptation. ECCV Workshops (3) 2016: 443-450 - [c49]Huijuan Xu, Kate Saenko:
Ask, Attend and Answer: Exploring Question-Guided Spatial Attention for Visual Question Answering. ECCV (7) 2016: 451-466 - [c48]Subhashini Venugopalan, Lisa Anne Hendricks, Raymond J. Mooney, Kate Saenko:
Improving LSTM-based Video Description with Linguistic Knowledge Mined from Text. EMNLP 2016: 1961-1966 - [c47]Xingchao Peng, Judy Hoffman, Stella X. Yu, Kate Saenko:
Fine-to-coarse knowledge transfer for low-res image classification. ICIP 2016: 3683-3687 - [c46]Marcus Gualtieri, Andreas ten Pas, Kate Saenko, Robert Platt Jr.:
High precision grasp pose detection in dense clutter. IROS 2016: 598-605 - [c45]Vasili Ramanishka, Abir Das, Dong Huk Park, Subhashini Venugopalan, Lisa Anne Hendricks, Marcus Rohrbach, Kate Saenko:
Multimodal Video Description. ACM Multimedia 2016: 1092-1096 - [c44]Marie-Francine Moens, Katerina Pastra, Kate Saenko, Tinne Tuytelaars:
Vision and Language Integration Meets Multimedia Fusion: Proceedings of ACM Multimedia 2016 Workshop. ACM Multimedia 2016: 1493 - [c43]Eric Tzeng, Coline Devin, Judy Hoffman, Chelsea Finn, Pieter Abbeel, Sergey Levine, Kate Saenko, Trevor Darrell:
Adapting Deep Visuomotor Representations with Weak Pairwise Constraints. WAFR 2016: 688-703 - 2015
- [c42]Baochen Sun, Kate Saenko:
Subspace Distribution Alignment for Unsupervised Domain Adaptation. BMVC 2015: 24.1-24.10 - [c41]Jeff Donahue, Lisa Anne Hendricks, Sergio Guadarrama, Marcus Rohrbach, Subhashini Venugopalan, Trevor Darrell, Kate Saenko:
Long-term recurrent convolutional networks for visual recognition and description. CVPR 2015: 2625-2634 - [c40]Judy Hoffman, Deepak Pathak, Trevor Darrell, Kate Saenko:
Detector discovery in the wild: Joint multiple instance and representation learning. CVPR 2015: 2883-2891 - [c39]Xingchao Peng, Baochen Sun, Karim Ali, Kate Saenko:
Learning Deep Object Detectors from 3D Models. ICCV 2015: 1278-1286 - [c38]Damian Mrowca, Marcus Rohrbach, Judy Hoffman, Ronghang Hu, Kate Saenko, Trevor Darrell:
Spatial Semantic Regularisation for Large Scale Object Detection. ICCV 2015: 2003-2011 - [c37]Eric Tzeng, Judy Hoffman, Trevor Darrell, Kate Saenko:
Simultaneous Deep Transfer Across Domains and Tasks. ICCV 2015: 4068-4076 - [c36]Subhashini Venugopalan, Marcus Rohrbach, Jeffrey Donahue, Raymond J. Mooney, Trevor Darrell, Kate Saenko:
Sequence to Sequence - Video to Text. ICCV 2015: 4534-4542 - [c35]Subhashini Venugopalan, Huijuan Xu, Jeff Donahue, Marcus Rohrbach, Raymond J. Mooney, Kate Saenko:
Translating Videos to Natural Language Using Deep Recurrent Neural Networks. HLT-NAACL 2015: 1494-1504 - [c34]Xingchao Peng, Baochen Sun, Karim Ali, Kate Saenko:
What Do Deep CNNs Learn About Objects? ICLR (Workshop) 2015 - 2014
- [c33]Baochen Sun, Kate Saenko:
From Virtual to Reality: Fast Adaptation of Virtual Object Detectors to Real Domains. BMVC 2014 - [c32]Jesse Thomason, Subhashini Venugopalan, Sergio Guadarrama, Kate Saenko, Raymond J. Mooney:
Integrating Language and Vision to Generate Natural Language Descriptions of Videos in the Wild. COLING 2014: 1218-1227 - [c31]Judy Hoffman, Trevor Darrell, Kate Saenko:
Continuous Manifold Based Adaptation for Evolving Visual Domains. CVPR 2014: 867-874 - [c30]Karim Ali, Kate Saenko:
Confidence-Rated Multiple Instance Boosting for Object Detection. CVPR 2014: 2433-2440 - [c29]Daniel Goehring, Judy Hoffman, Erik Rodner, Kate Saenko, Trevor Darrell:
Interactive adaptation of real-time object detectors. ICRA 2014: 1282-1289 - [c28]Judy Hoffman, Sergio Guadarrama, Eric Tzeng, Ronghang Hu, Jeff Donahue, Ross B. Girshick, Trevor Darrell, Kate Saenko:
LSDA: Large Scale Detection through Adaptation. NIPS 2014: 3536-3544 - [c27]Sergio Guadarrama, Erik Rodner, Kate Saenko, Ning Zhang, Ryan Farrell, Jeff Donahue, Trevor Darrell:
Open-vocabulary Object Retrieval. Robotics: Science and Systems 2014 - [c26]Judy Hoffman, Eric Tzeng, Jeff Donahue, Yangqing Jia, Kate Saenko, Trevor Darrell:
One-Shot Adaptation of Supervised Deep Convolutional Models. ICLR (Workshop Poster) 2014 - 2013
- [c25]Niveda Krishnamoorthy, Girish Malkarnenkar, Raymond J. Mooney, Kate Saenko, Sergio Guadarrama:
Generating Natural-Language Video Descriptions Using Text-Mined Knowledge. AAAI 2013: 541-547 - [c24]Jeff Donahue, Judy Hoffman, Erik Rodner, Kate Saenko, Trevor Darrell:
Semi-supervised Domain Adaptation with Instance Constraints. CVPR 2013: 668-675 - [c23]Sergio Guadarrama, Niveda Krishnamoorthy, Girish Malkarnenkar, Subhashini Venugopalan, Raymond J. Mooney, Trevor Darrell, Kate Saenko:
YouTube2Text: Recognizing and Describing Arbitrary Activities Using Semantic Hierarchies and Zero-Shot Recognition. ICCV 2013: 2712-2719 - [c22]Eric McCann, Mikhail S. Medvedev, Daniel J. Brooks, Kate Saenko:
"Off the grid": Self-contained landmarks for improved indoor probabilistic localization. TePRA 2013: 1-6 - [c21]Judy Hoffman, Erik Rodner, Jeff Donahue, Kate Saenko, Trevor Darrell:
Efficient Learning of Domain-invariant Image Representations. ICLR (Poster) 2013 - 2012
- [c20]Ying Xiong, Kate Saenko, Trevor Darrell, Todd E. Zickler:
From pixels to physics: Probabilistic color de-rendering. CVPR 2012: 358-365 - [c19]Benjamin Packer, Kate Saenko, Daphne Koller:
A combined pose, object, and feature model for action understanding. CVPR 2012: 1378-1385 - [c18]Judy Hoffman, Brian Kulis, Trevor Darrell, Kate Saenko:
Discovering Latent Domains for Multisource Domain Adaptation. ECCV (2) 2012: 702-715 - 2011
- [c17]Trevor Owens, Kate Saenko, Ayan Chakrabarti, Ying Xiong, Todd E. Zickler, Trevor Darrell:
Learning object color models from multi-view constraints. CVPR 2011: 169-176 - [c16]Brian Kulis, Kate Saenko, Trevor Darrell:
What you saw is not what you get: Domain adaptation using asymmetric kernel transforms. CVPR 2011: 1785-1792 - [c15]Tinne Tuytelaars, Mario Fritz, Kate Saenko, Trevor Darrell:
The NBNN kernel. ICCV 2011: 1824-1831 - [c14]Allison Janoch, Sergey Karayev, Yangqing Jia, Jonathan T. Barron, Mario Fritz, Kate Saenko, Trevor Darrell:
A category-level 3-D object dataset: Putting the Kinect to work. ICCV Workshops 2011: 1168-1174 - [c13]Kate Saenko, Sergey Karayev, Yangqing Jia, Alex Shyr, Allison Janoch, Jonathan Long, Mario Fritz, Trevor Darrell:
Practical 3-D object detection using category and instance-level appearance models. IROS 2011: 793-800 - 2010
- [c12]Kate Saenko, Brian Kulis, Mario Fritz, Trevor Darrell:
Adapting Visual Category Models to New Domains. ECCV (4) 2010: 213-226 - [c11]Mario Fritz, Kate Saenko, Trevor Darrell:
Size Matters: Metric Visual Search Constraints from Monocular Metadata. NIPS 2010: 622-630 - 2009
- [c10]Kate Saenko, Trevor Darrell:
Filtering Abstract Senses From Image Search Results. NIPS 2009: 1589-1597 - 2008
- [c9]Kate Saenko, Trevor Darrell:
Unsupervised Learning of Visual Sense Models for Polysemous Words. NIPS 2008: 1393-1400 - 2007
- [c8]Karen Livescu, Özgür Çetin, Mark Hasegawa-Johnson, Simon King, Chris D. Bartels, Nash M. Borges, Arthur Kantor, Partha Lal, Lisa Yung, Ari Bezman, Stephen Dawson-Haggerty, Bronwyn Woods, Joe Frankel, Mathew Magimai-Doss, Kate Saenko:
Articulatory Feature-Based Methods for Acoustic and Audio-Visual Speech Recognition: Summary from the 2006 JHU Summer workshop. ICASSP (4) 2007: 621-624 - [c7]Kate Saenko, Trevor Darrell:
Object Category Recognition Using Probabilistic Fusion of Speech and Image Classifiers. MLMI 2007: 36-47 - 2006
- [c6]C. Mario Christoudias, Kate Saenko, Louis-Philippe Morency, Trevor Darrell:
Co-Adaptation of audio-visual speech and gesture classifiers. ICMI 2006: 84-91 - [c5]Kate Saenko, Karen Livescu:
An Asynchronous DBN for Audio-Visual speech Recognition. SLT 2006: 154-157 - 2005
- [c4]Kate Saenko, Karen Livescu, James R. Glass, Trevor Darrell:
Production domain modeling of pronunciation for visual speech recognition. ICASSP (5) 2005: 473-476 - [c3]Kate Saenko, Karen Livescu, Michael Siracusa, Kevin W. Wilson, James R. Glass, Trevor Darrell:
Visual Speech Recognition with Loosely Synchronized Feature Streams. ICCV 2005: 1424-1431 - 2004
- [c2]Kate Saenko, Trevor Darrell, James R. Glass:
Articulatory features for robust visual speech recognition. ICMI 2004: 152-158 - [c1]Timothy J. Hazen, Kate Saenko, Chia-Hao La, James R. Glass:
A segment-based audio-visual speech recognizer: data collection, development, and initial experiments. ICMI 2004: 235-242
Parts in Books or Collections
- 2017
- [p3]Baochen Sun, Jiashi Feng, Kate Saenko:
Correlation Alignment for Unsupervised Domain Adaptation. Domain Adaptation in Computer Vision Applications 2017: 153-171 - [p2]Judy Hoffman, Eric Tzeng, Trevor Darrell, Kate Saenko:
Simultaneous Deep Transfer Across Domains and Tasks. Domain Adaptation in Computer Vision Applications 2017: 173-187 - 2013
- [p1]Allison Janoch, Sergey Karayev, Yangqing Jia, Jonathan T. Barron, Mario Fritz, Kate Saenko, Trevor Darrell:
A Category-Level 3D Object Dataset: Putting the Kinect to Work. Consumer Depth Cameras for Computer Vision 2013: 141-165
Editorship
- 2023
- [e2]Alice Oh, Tristan Naumann, Amir Globerson, Kate Saenko, Moritz Hardt, Sergey Levine:
Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023. 2023 [contents] - 2016
- [e1]Marie-Francine Moens, Katerina Pastra, Kate Saenko, Tinne Tuytelaars:
Proceedings of the 2016 ACM workshop on Vision and Language Integration Meets Multimedia Fusion, iV&L-MM@MM 2016, Amsterdam, Netherlands, October 16, 2016. ACM 2016, ISBN 978-1-4503-4519-4 [contents]
Informal and Other Publications
- 2024
- [i165]Samarth Mishra, Kate Saenko, Venkatesh Saligrama:
SynCDR : Training Cross Domain Retrieval Models with Synthetic Data. CoRR abs/2401.00420 (2024) - [i164]Maan Qraitem, Nazia Tasnim, Piotr Teterwak, Kate Saenko, Bryan A. Plummer:
Vision-LLMs Can Fool Themselves with Self-Generated Typographic Attacks. CoRR abs/2402.00626 (2024) - [i163]Reuben Tan, Ximeng Sun, Ping Hu, Jui-Hsien Wang, Hanieh Deilamsalehy, Bryan A. Plummer, Bryan Russell, Kate Saenko:
Koala: Key frame-conditioned long video-LLM. CoRR abs/2404.04346 (2024) - [i162]Vitali Petsiuk, Kate Saenko:
Concept Arithmetics for Circumventing Concept Inhibition in Diffusion Models. CoRR abs/2404.13706 (2024) - [i161]Florian Bordes, Richard Yuanzhe Pang, Anurag Ajay, Alexander C. Li, Adrien Bardes, Suzanne Petryk, Oscar Mañas, Zhiqiu Lin, Anas Mahmoud, Bargav Jayaraman, Mark Ibrahim, Melissa Hall, Yunyang Xiong, Jonathan Lebensold, Candace Ross, Srihari Jayakumar, Chuan Guo, Diane Bouchacourt, Haider Al-Tahan, Karthik Padthe, Vasu Sharma, Hu Xu, Xiaoqing Ellen Tan, Megan Richards, Samuel Lavoie, Pietro Astolfi, Reyhane Askari Hemmat, Jun Chen, Kushal Tirumala, Rim Assouel, Mazda Moayeri, Arjang Talattof, Kamalika Chaudhuri, Zechun Liu, Xilun Chen, Quentin Garrido, Karen Ullrich, Aishwarya Agrawal, Kate Saenko, Asli Celikyilmaz, Vikas Chandra:
An Introduction to Vision-Language Modeling. CoRR abs/2405.17247 (2024) - [i160]Maan Qraitem, Piotr Teterwak, Kate Saenko, Bryan A. Plummer:
SLANT: Spurious Logo ANalysis Toolkit. CoRR abs/2406.01449 (2024) - [i159]Andrea Burns, Kate Saenko, Bryan A. Plummer:
Tell Me What's Next: Textual Foresight for Generic UI Representations. CoRR abs/2406.07822 (2024) - [i158]Eunice Yiu, Maan Qraitem, Charlie Wong, Anisa Noor Majhi, Yutong Bai, Shiry Ginosar, Alison Gopnik, Kate Saenko:
KiVA: Kid-inspired Visual Analogies for Testing Large Multimodal Models. CoRR abs/2407.17773 (2024) - 2023
- [i157]Bassel El Mabsout, Shahin Roozkhosh, Siddharth Mysore, Kate Saenko, Renato Mancuso:
The SwaNNFlight System: On-the-Fly Sim-to-Real Adaptation via Anchored Learning. CoRR abs/2301.06987 (2023) - [i156]Kuniaki Saito, Kihyuk Sohn, Xiang Zhang, Chun-Liang Li, Chen-Yu Lee, Kate Saenko, Tomas Pfister:
Pic2Word: Mapping Pictures to Words for Zero-shot Composed Image Retrieval. CoRR abs/2302.03084 (2023) - [i155]Dina Bashkirova, José Lezama, Kihyuk Sohn, Kate Saenko, Irfan Essa:
MaskSketch: Unpaired Structure-guided Masked Image Generation. CoRR abs/2302.05496 (2023) - [i154]Kuniaki Saito, Donghyun Kim, Piotr Teterwak, Rogério Feris, Kate Saenko:
Mind the Backbone: Minimizing Backbone Distortion for Robust Object Detection. CoRR abs/2303.14744 (2023) - [i153]Dina Bashkirova, Samarth Mishra, Diala Lteif, Piotr Teterwak, Donghyun Kim, Fadi M. Alladkani, James Akl, Berk Çalli, Sarah Adel Bargal, Kate Saenko, Daehan Kim, Minseok Seo, Youngjin Jeon, Dong-Geol Choi, Shahaf Ettedgui, Raja Giryes, Shady Abu-Hussein, Binhui Xie, Shuang Li:
VisDA 2022 Challenge: Domain Adaptation for Industrial Waste Sorting. CoRR abs/2303.14828 (2023) - [i152]Reuben Tan, Arijit Ray, Andrea Burns, Bryan A. Plummer, Justin Salamon, Oriol Nieto, Bryan Russell, Kate Saenko:
Language-Guided Audio-Visual Source Separation via Trimodal Consistency. CoRR abs/2303.16342 (2023) - [i151]Ximeng Sun, Pengchuan Zhang, Peizhao Zhang, Hardik Shah, Kate Saenko, Xide Xia:
DIME-FM: DIstilling Multimodal and Efficient Foundation Models. CoRR abs/2303.18232 (2023) - [i150]Piotr Teterwak, Kuniaki Saito, Theodoros Tsiligkaridis, Kate Saenko, Bryan A. Plummer:
ERM++: An Improved Baseline for Domain Generalization. CoRR abs/2304.01973 (2023) - [i149]Andrea Burns, Krishna Srinivasan, Joshua Ainslie, Geoff Brown, Bryan A. Plummer, Kate Saenko, Jianmo Ni, Mandy Guo:
A Suite of Generative Tasks for Multi-Level Multimodal Webpage Understanding. CoRR abs/2305.03668 (2023) - [i148]Arijit Ray, Filip Radenovic, Abhimanyu Dubey, Bryan A. Plummer, Ranjay Krishna, Kate Saenko:
COLA: How to adapt vision-language models to Compose Objects Localized with Attributes? CoRR abs/2305.03689 (2023) - [i147]Andrea Burns, Krishna Srinivasan, Joshua Ainslie, Geoff Brown, Bryan A. Plummer, Kate Saenko, Jianmo Ni, Mandy Guo:
WikiWeb2M: A Page-Level Multimodal Wikipedia Dataset. CoRR abs/2305.05432 (2023) - [i146]Ariel N. Lee, Sarah Adel Bargal, Janavi Kasera, Stan Sclaroff, Kate Saenko, Nataniel Ruiz:
Hardwiring ViT Patch Selectivity into CNNs using Patch Mixing. CoRR abs/2306.17848 (2023) - [i145]Reuben Tan, Matthias De Lange, Michael L. Iuzzolino, Bryan A. Plummer, Kate Saenko, Karl Ridgeway, Lorenzo Torresani:
Multiscale Video Pretraining for Long-Term Activity Forecasting. CoRR abs/2307.12854 (2023) - [i144]Ping Hu, Ximeng Sun, Stan Sclaroff, Kate Saenko:
DualCoOp++: Fast and Effective Adaptation to Multi-Label Recognition with Limited Annotations. CoRR abs/2308.01890 (2023) - [i143]Maan Qraitem, Kate Saenko, Bryan A. Plummer:
From Fake to Real (FFR): A two-stage training pipeline for mitigating spurious correlations with synthetic data. CoRR abs/2308.04553 (2023) - [i142]Ximeng Sun, Kihyuk Sohn, Kate Saenko, Clayton Mellina, Xiao Bian:
Label Budget Allocation in Multi-Task Learning. CoRR abs/2308.12949 (2023) - [i141]Katherine Deng, Arijit Ray, Reuben Tan, Saadia Gabriel, Bryan A. Plummer, Kate Saenko:
Socratis: Are large multimodal models emotionally aware? CoRR abs/2308.16741 (2023) - [i140]Ping Hu, Simon Niklaus, Lu Zhang, Stan Sclaroff, Kate Saenko:
Video Frame Interpolation with Many-to-many Splatting and Spatial Selective Refinement. CoRR abs/2310.18946 (2023) - [i139]Dina Bashkirova, Arijit Ray, Rupayan Mallick, Sarah Adel Bargal, Jianming Zhang, Ranjay Krishna, Kate Saenko:
Lasagna: Layered Score Distillation for Disentangled Object Relighting. CoRR abs/2312.00833 (2023) - [i138]Piotr Teterwak, Soren Nelson, Nikoli Dryden, Dina Bashkirova, Kate Saenko, Bryan A. Plummer:
Learning to Compose SuperWeights for Neural Parameter Allocation Search. CoRR abs/2312.01274 (2023) - [i137]Piotr Teterwak, Ximeng Sun, Bryan A. Plummer, Kate Saenko, Ser-Nam Lim:
CLAMP: Contrastive LAnguage Model Prompt-tuning. CoRR abs/2312.01629 (2023) - 2022
- [i136]Julius Frost, Olivia Watkins, Eric Weiner, Pieter Abbeel, Trevor Darrell, Bryan A. Plummer, Kate Saenko:
Explaining Reinforcement Learning Policies through Counterfactual Trajectories. CoRR abs/2201.12462 (2022) - [i135]Andrea Burns, Deniz Arsan, Sanjna Agrawal, Ranjitha Kumar, Kate Saenko, Bryan A. Plummer:
Interactive Mobile App Navigation with Uncertain or Under-specified Natural Language Commands. CoRR abs/2202.02312 (2022) - [i134]Jack Hessel, Jena D. Hwang, Jae Sung Park, Rowan Zellers, Chandra Bhagavatula, Anna Rohrbach, Kate Saenko, Yejin Choi:
The Abduction of Sherlock Holmes: A Dataset for Visual Abductive Reasoning. CoRR abs/2202.04800 (2022) - [i133]Donghyun Kim, Kaihong Wang, Stan Sclaroff, Kate Saenko:
A Broad Study of Pre-training for Domain Generalization and Adaptation. CoRR abs/2203.11819 (2022) - [i132]Donghyun Kim, Kaihong Wang, Kate Saenko, Margrit Betke, Stan Sclaroff:
A Unified Framework for Domain Adaptive Pose Estimation. CoRR abs/2204.00172 (2022) - [i131]Ping Hu, Simon Niklaus, Stan Sclaroff, Kate Saenko:
Many-to-many Splatting for Efficient Video Frame Interpolation. CoRR abs/2204.03513 (2022) - [i130]Quanfu Fan, Donghyun Kim, Chun-Fu Chen, Stan Sclaroff, Kate Saenko, Sarah Adel Bargal:
Temporal Relevance Analysis for Video Action Models. CoRR abs/2204.11929 (2022) - [i129]Kuniaki Saito, Kihyuk Sohn, Xiang Zhang, Chun-Liang Li, Chen-Yu Lee, Kate Saenko, Tomas Pfister:
Prefix Conditioning Unifies Language and Label Supervision. CoRR abs/2206.01125 (2022) - [i128]Ximeng Sun, Ping Hu, Kate Saenko:
DualCoOp: Fast Adaptation to Multi-Label Recognition with Limited Annotations. CoRR abs/2206.09541 (2022) - [i127]Reuben Tan, Bryan A. Plummer, Kate Saenko, J. P. Lewis, Avneesh Sud, Thomas Leung:
NewsStories: Illustrating articles with visual summaries. CoRR abs/2207.13061 (2022) - [i126]Amit Alfassy, Assaf Arbelle, Oshri Halimi, Sivan Harary, Roei Herzig, Eli Schwartz, Rameswar Panda, Michele Dolfi, Christoph Auer, Kate Saenko, Peter W. J. Staar, Rogério Feris, Leonid Karlinsky:
FETA: Towards Specializing Foundation Models for Expert Task Applications. CoRR abs/2209.03648 (2022) - [i125]Maan Qraitem, Kate Saenko, Bryan A. Plummer:
Bias Mimicking: A Simple Sampling Approach for Bias Mitigation. CoRR abs/2209.15605 (2022) - [i124]Vitali Petsiuk, Alexander E. Siemenn, Saisamrit Surbehera, Zad Chin, Keith Tyser, Gregory Hunter, Arvind Raghavan, Yann Hicke, Bryan A. Plummer, Ori Kerret, Tonio Buonassisi, Kate Saenko, Armando Solar-Lezama, Iddo Drori:
Human Evaluation of Text-to-Image Models on a Multi-Task Benchmark. CoRR abs/2211.12112 (2022) - [i123]Kaihong Wang, Donghyun Kim, Rogério Feris, Kate Saenko, Margrit Betke:
Exploring Consistency in Cross-Domain Transformer for Domain Adaptive Semantic Segmentation. CoRR abs/2211.14703 (2022) - [i122]Nataniel Ruiz, Sarah Adel Bargal, Cihang Xie, Kate Saenko, Stan Sclaroff:
Finding Differences Between Transformers and ConvNets Using Counterfactual Simulation Testing. CoRR abs/2211.16499 (2022) - 2021
- [i121]Samarth Mishra, Kate Saenko, Venkatesh Saligrama:
Surprisingly Simple Semi-Supervised Domain Adaptation with Pretraining and Consistency. CoRR abs/2101.12727 (2021) - [i120]Ankit Singh, Omprakash Chakraborty, Ashutosh Varshney, Rameswar Panda, Rogério Feris, Kate Saenko, Abir Das:
Semi-Supervised Action Recognition with Temporal Contrastive Learning. CoRR abs/2102.02751 (2021) - [i119]Yue Meng, Rameswar Panda, Chung-Ching Lin, Prasanna Sattigeri, Leonid Karlinsky, Kate Saenko, Aude Oliva, Rogério Feris:
AdaFuse: Adaptive Temporal Fusion Network for Efficient Action Recognition. CoRR abs/2102.05775 (2021) - [i118]Bowen Pan, Rameswar Panda, Camilo Fosco, Chung-Ching Lin, Alex Andonian, Yue Meng, Kate Saenko, Aude Oliva, Rogério Feris:
VA-RED2: Video Adaptive Redundancy Reduction. CoRR abs/2102.07887 (2021) - [i117]Siddharth Mysore, Bassel Mabsout, Renato Mancuso, Kate Saenko:
Good Actors can come in Smaller Sizes: A Case Study on the Value of Actor-Critic Asymmetry. CoRR abs/2102.11893 (2021) - [i116]Ximeng Sun, Rameswar Panda, Chun-Fu Chen, Naigang Wang, Bowen Pan, Kailash Gopalakrishnan, Aude Oliva, Rogério Feris, Kate Saenko:
All at Once Network Quantization via Collaborative Knowledge Transfer. CoRR abs/2103.01435 (2021) - [i115]Dina Bashkirova, Ben Usman, Kate Saenko:
Evaluation of Correctness in Unsupervised Many-to-Many Image Translation. CoRR abs/2103.15727 (2021) - [i114]Kuniaki Saito, Kate Saenko:
OVANet: One-vs-All Network for Universal Domain Adaptation. CoRR abs/2104.03344 (2021) - [i113]Andrea Burns, Deniz Arsan, Sanjna Agrawal, Ranjitha Kumar, Kate Saenko, Bryan A. Plummer:
Mobile App Tasks with Iterative Feedback (MoTIF): Addressing Task Feasibility in Interactive Visual Environments. CoRR abs/2104.08560 (2021) - [i112]Assaf Arbelle, Sivan Doveh, Amit Alfassy, Joseph Shtok, Guy Lev, Eli Schwartz, Hilde Kuehne, Hila Barak Levi, Prasanna Sattigeri, Rameswar Panda, Chun-Fu Chen, Alex M. Bronstein, Kate Saenko, Shimon Ullman, Raja Giryes, Rogério Feris, Leonid Karlinsky:
Detector-Free Weakly Supervised Grounding by Separation. CoRR abs/2104.09829 (2021) - [i111]Rameswar Panda, Chun-Fu Chen, Quanfu Fan, Ximeng Sun, Kate Saenko, Aude Oliva, Rogério Feris:
AdaMML: Adaptive Multi-Modal Learning for Efficient Video Recognition. CoRR abs/2105.05165 (2021) - [i110]Kuniaki Saito, Donghyun Kim, Kate Saenko:
OpenMatch: Open-set Consistency Regularization for Semi-supervised Learning with Outliers. CoRR abs/2105.14148 (2021) - [i109]Dina Bashkirova, Ziliang Zhu, James Akl, Fadi M. Alladkani, Ping Hu, Vitaly Ablavsky, Berk Çalli, Sarah Adel Bargal, Kate Saenko:
ZeroWaste Dataset: Towards Automated Waste Recycling. CoRR abs/2106.02740 (2021) - [i108]Spencer Whitehead, Hui Wu, Heng Ji, Rogério Feris, Kate Saenko:
Separating Skills and Concepts for Novel Visual Question Answering. CoRR abs/2107.09106 (2021) - [i107]Dina Bashkirova, Dan Hendrycks, Donghyun Kim, Samarth Mishra, Kate Saenko, Kuniaki Saito, Piotr Teterwak, Ben Usman:
VisDA-2021 Competition Universal Domain Adaptation to Improve Performance on Out-of-Distribution Data. CoRR abs/2107.11011 (2021) - [i106]Ben Usman, Andrea Tagliasacchi, Kate Saenko, Avneesh Sud:
MetaPose: Fast 3D Pose from Multiple Views without 3D Supervision. CoRR abs/2108.04869 (2021) - [i105]Ximeng Sun, Rameswar Panda, Chun-Fu Chen, Aude Oliva, Rogério Feris, Kate Saenko:
Dynamic Network Quantization for Efficient Video Inference. CoRR abs/2108.10394 (2021) - [i104]Kuniaki Saito, Donghyun Kim, Piotr Teterwak, Stan Sclaroff, Trevor Darrell, Kate Saenko:
Tune it the Right Way: Unsupervised Validation of Domain Adaptation via Soft Neighborhood Density. CoRR abs/2108.10860 (2021) - [i103]Donghyun Kim, Yi-Hsuan Tsai, Bingbing Zhuang, Xiang Yu, Stan Sclaroff, Kate Saenko, Manmohan Chandraker:
Learning Cross-modal Contrastive Features for Video Domain Adaptation. CoRR abs/2108.11974 (2021) - [i102]Reuben Tan, Bryan A. Plummer, Kate Saenko, Hailin Jin, Bryan Russell:
Look at What I'm Doing: Self-Supervised Spatial Grounding of Narrations in Instructional Videos. CoRR abs/2110.10596 (2021) - [i101]Aadarsh Sahoo, Rutav Shah, Rameswar Panda, Kate Saenko, Abir Das:
Contrast and Mix: Temporal Contrastive Video Domain Adaptation with Background Mixing. CoRR abs/2110.15128 (2021) - [i100]Ben Usman, Dina Bashkirova, Kate Saenko:
Disentangled Unsupervised Image Translation via Restricted Information Flow. CoRR abs/2111.13279 (2021) - [i99]Samarth Mishra, Rameswar Panda, Cheng Perng Phoo, Chun-Fu Chen, Leonid Karlinsky, Kate Saenko, Venkatesh Saligrama, Rogério Schmidt Feris:
Task2Sim : Towards Effective Pre-training and Transfer from Synthetic Data. CoRR abs/2112.00054 (2021) - [i98]Kuniaki Saito, Ping Hu, Trevor Darrell, Kate Saenko:
Learning to Detect Every Thing in an Open World. CoRR abs/2112.01698 (2021) - [i97]Sivan Harary, Eli Schwartz, Assaf Arbelle, Peter W. J. Staar, Shady Abu-Hussein, Elad Amrani, Roei Herzig, Amit Alfassy, Raja Giryes, Hilde Kuehne, Dina Katabi, Kate Saenko, Rogério Feris, Leonid Karlinsky:
Unsupervised Domain Generalization by Learning a Bridge Across Domains. CoRR abs/2112.02300 (2021) - [i96]Shiori Sagawa, Pang Wei Koh, Tony Lee, Irena Gao, Sang Michael Xie, Kendrick Shen, Ananya Kumar, Weihua Hu, Michihiro Yasunaga, Henrik Marklund, Sara Beery, Etienne David, Ian Stavness, Wei Guo, Jure Leskovec, Kate Saenko, Tatsunori Hashimoto, Sergey Levine, Chelsea Finn, Percy Liang:
Extending the WILDS Benchmark for Unsupervised Adaptation. CoRR abs/2112.05090 (2021) - 2020
- [i95]Kuniaki Saito, Donghyun Kim, Stan Sclaroff, Kate Saenko:
Universal Domain Adaptation through Self Supervision. CoRR abs/2002.07953 (2020) - [i94]Andrea Zunino, Sarah Adel Bargal, Riccardo Volpi, Mehrnoosh Sameki, Jianming Zhang, Stan Sclaroff, Vittorio Murino, Kate Saenko:
Explainable Deep Classification Models for Domain Generalization. CoRR abs/2003.06498 (2020) - [i93]Donghyun Kim, Kuniaki Saito, Tae-Hyun Oh, Bryan A. Plummer, Stan Sclaroff, Kate Saenko:
Cross-domain Self-supervised Learning for Domain Adaptation with Few Source Labels. CoRR abs/2003.08264 (2020) - [i92]Ben Usman, Nick Dufour, Avneesh Sud, Kate Saenko:
Log-Likelihood Ratio Minimizing Flows: Towards Robust and Quantifiable Neural Distribution Alignment. CoRR abs/2003.12170 (2020) - [i91]Huijuan Xu, Ximeng Sun, Eric Tzeng, Abir Das, Kate Saenko, Trevor Darrell:
Revisiting Few-shot Activity Detection with Class Similarity Control. CoRR abs/2004.00137 (2020) - [i90]Huijuan Xu, Lizhi Yang, Stan Sclaroff, Kate Saenko, Trevor Darrell:
Spatio-Temporal Action Detection with Multi-Object Interaction. CoRR abs/2004.00180 (2020) - [i89]Andrea Burns, Donghyun Kim, Derry Wijaya, Kate Saenko, Bryan A. Plummer:
Learning to Scale Multilingual Representations for Vision-Language Tasks. CoRR abs/2004.04312 (2020) - [i88]Ulrich Viereck, Kate Saenko, Robert Platt Jr.:
Learning visual servo policies via planner cloning. CoRR abs/2005.11810 (2020) - [i87]Vitali Petsiuk, Rajiv Jain, Varun Manjunatha, Vlad I. Morariu, Ashutosh Mehra, Vicente Ordonez, Kate Saenko:
Black-box Explanation of Object Detectors via Saliency Maps. CoRR abs/2006.03204 (2020) - [i86]Bryan A. Plummer, Nikoli Dryden, Julius Frost, Torsten Hoefler, Kate Saenko:
Shapeshifter Networks: Cross-layer Parameter Sharing for Scalable and Effective Deep Learning. CoRR abs/2006.10598 (2020) - [i85]Ping Hu, Federico Perazzi, Fabian Caba Heilbron, Oliver Wang, Zhe Lin, Kate Saenko, Stan Sclaroff:
Real-time Semantic Segmentation with Fast Attention. CoRR abs/2007.03815 (2020) - [i84]Kuniaki Saito, Kate Saenko, Ming-Yu Liu:
COCO-FUNIT: Few-Shot Unsupervised Image Translation with a Content Conditioned Style Encoder. CoRR abs/2007.07431 (2020) - [i83]Xingchao Peng, Yichen Li, Kate Saenko:
Domain2Vec: Domain Embedding for Unsupervised Domain Adaptation. CoRR abs/2007.09257 (2020) - [i82]Yue Meng, Chung-Ching Lin, Rameswar Panda, Prasanna Sattigeri, Leonid Karlinsky, Aude Oliva, Kate Saenko, Rogério Feris:
AR-Net: Adaptive Frame Resolution for Efficient Action Recognition. CoRR abs/2007.15796 (2020) - [i81]Donghyun Kim, Kuniaki Saito, Kate Saenko, Stan Sclaroff, Bryan A. Plummer:
Self-supervised Visual Attribute Learning for Fashion Compatibility. CoRR abs/2008.00348 (2020) - [i80]Reuben Tan, Bryan A. Plummer, Kate Saenko:
Detecting Cross-Modal Inconsistency to Defend Against Neural Fake News. CoRR abs/2009.07698 (2020) - [i79]Baifeng Shi, Judy Hoffman, Kate Saenko, Trevor Darrell, Huijuan Xu:
Auxiliary Task Reweighting for Minimum-data Learning. CoRR abs/2010.08244 (2020) - [i78]Viraj Prabhu, Arjun Chandrasekaran, Kate Saenko, Judy Hoffman:
Active Domain Adaptation via Clustering Uncertainty-weighted Embeddings. CoRR abs/2010.08666 (2020) - [i77]Baifeng Shi, Qi Dai, Judy Hoffman, Kate Saenko, Trevor Darrell, Huijuan Xu:
Temporal Action Detection with Multi-level Supervision. CoRR abs/2011.11893 (2020) - [i76]Spencer Whitehead, Hui Wu, Yi Ren Fung, Heng Ji, Rogério Schmidt Feris, Kate Saenko:
Learning from Lexical Perturbations for Consistent Visual Question Answering. CoRR abs/2011.13406 (2020) - [i75]Aadarsh Sahoo, Rameswar Panda, Rogério Feris, Kate Saenko, Abir Das:
Select, Label, and Mix: Learning Discriminative Invariant Feature Representations for Partial Domain Adaptation. CoRR abs/2012.03358 (2020) - [i74]Guy Bukchin, Eli Schwartz, Kate Saenko, Ori Shahar, Rogério Feris, Raja Giryes, Leonid Karlinsky:
Fine-grained Angular Contrastive Learning with Coarse Labels. CoRR abs/2012.03515 (2020) - [i73]Siddharth Mysore, Bassel Mabsout, Renato Mancuso, Kate Saenko:
Regularizing Action Policies for Smooth Control with Reinforcement Learning. CoRR abs/2012.06644 (2020) - [i72]Siddharth Mysore, Bassel Mabsout, Kate Saenko, Renato Mancuso:
How to Train your Quadrotor: A Framework for Consistently Smooth and Responsive Flight Control via Reinforcement Learning. CoRR abs/2012.06656 (2020) - 2019
- [i71]Ben Usman, Nick Dufour, Kate Saenko, Chris Bregler:
PuppetGAN: Transferring Disentangled Properties from Synthetic to Real Images. CoRR abs/1901.10024 (2019) - [i70]Kuniaki Saito, Donghyun Kim, Stan Sclaroff, Trevor Darrell, Kate Saenko:
Semi-supervised Domain Adaptation via Minimax Entropy. CoRR abs/1904.06487 (2019) - [i69]Xingchao Peng, Zijun Huang, Ximeng Sun, Kate Saenko:
Domain Agnostic Learning with Disentangled Representations. CoRR abs/1904.12347 (2019) - [i68]Ronghang Hu, Anna Rohrbach, Trevor Darrell, Kate Saenko:
Language-Conditioned Graph Networks for Relational Reasoning. CoRR abs/1905.04405 (2019) - [i67]Bryan A. Plummer, Mariya I. Vasileva, Vitali Petsiuk, Kate Saenko, David A. Forsyth:
Why do These Match? Explaining the Behavior of Image Similarity Models. CoRR abs/1905.10797 (2019) - [i66]Ronghang Hu, Daniel Fried, Anna Rohrbach, Dan Klein, Trevor Darrell, Kate Saenko:
Are You Looking? Grounding to Multiple Modalities in Vision-and-Language Navigation. CoRR abs/1906.00347 (2019) - [i65]Huijuan Xu, Abir Das, Kate Saenko:
Two-Stream Region Convolutional 3D Network for Temporal Activity Detection. CoRR abs/1906.02182 (2019) - [i64]Ping Hu, Ximeng Sun, Kate Saenko, Stan Sclaroff:
Weakly-supervised Compositional FeatureAggregation for Few-shot Recognition. CoRR abs/1906.04833 (2019) - [i63]Dina Bashkirova, Ben Usman, Kate Saenko:
Adversarial Self-Defense for Cycle-Consistent GANs. CoRR abs/1908.01517 (2019) - [i62]Andrea Burns, Reuben Tan, Kate Saenko, Stan Sclaroff, Bryan A. Plummer:
Language Features Matter: Effective Language Representations for Vision-Language Tasks. CoRR abs/1908.06327 (2019) - [i61]Reuben Tan, Mariya I. Vasileva, Kate Saenko, Bryan A. Plummer:
Learning Similarity Conditions Without Explicit Supervision. CoRR abs/1908.08589 (2019) - [i60]Donghyun Kim, Kuniaki Saito, Kate Saenko, Stan Sclaroff, Bryan A. Plummer:
MULE: Multimodal Universal Language Embedding. CoRR abs/1909.03493 (2019) - [i59]Reuben Tan, Huijuan Xu, Kate Saenko, Bryan A. Plummer:
wMAN: Weakly-supervised Moment Alignment Network for Text-based Video Segment Retrieval. CoRR abs/1909.13784 (2019) - [i58]Shuhan Tan, Xingchao Peng, Kate Saenko:
Generalized Domain Adaptation with Covariate and Label Shift CO-ALignment. CoRR abs/1910.10320 (2019) - [i57]Xingchao Peng, Zijun Huang, Yizhe Zhu, Kate Saenko:
Federated Adversarial Domain Adaptation. CoRR abs/1911.02054 (2019) - 2018
- [i56]Yancheng Bai, Huijuan Xu, Kate Saenko, Bernard Ghanem:
Contextual Multi-Scale Region Convolutional 3D Network for Activity Detection. CoRR abs/1801.09184 (2018) - [i55]Huijuan Xu, Boyang Li, Vasili Ramanishka, Leonid Sigal, Kate Saenko:
Joint Event Detection and Description in Continuous Video Streams. CoRR abs/1802.10250 (2018) - [i54]Huijuan Xu, Kun He, Leonid Sigal, Stan Sclaroff, Kate Saenko:
Text-to-Clip Video Retrieval with Early Fusion and Re-Captioning. CoRR abs/1804.05113 (2018) - [i53]Daniel Fried, Ronghang Hu, Volkan Cirik, Anna Rohrbach, Jacob Andreas, Louis-Philippe Morency, Taylor Berg-Kirkpatrick, Kate Saenko, Dan Klein, Trevor Darrell:
Speaker-Follower Models for Vision-and-Language Navigation. CoRR abs/1806.02724 (2018) - [i52]Dina Bashkirova, Ben Usman, Kate Saenko:
Unsupervised Video-to-Video Translation. CoRR abs/1806.03698 (2018) - [i51]Vitali Petsiuk, Abir Das, Kate Saenko:
RISE: Randomized Input Sampling for Explanation of Black-box Models. CoRR abs/1806.07421 (2018) - [i50]Xingchao Peng, Ben Usman, Kuniaki Saito, Neela Kaushik, Judy Hoffman, Kate Saenko:
Syn2Real: A New Benchmark forSynthetic-to-Real Visual Domain Adaptation. CoRR abs/1806.09755 (2018) - [i49]Lisa Anne Hendricks, Kaylee Burns, Kate Saenko, Trevor Darrell, Anna Rohrbach:
Women also Snowboard: Overcoming Bias in Captioning Models (Extended Abstract). CoRR abs/1807.00517 (2018) - [i48]Ronghang Hu, Jacob Andreas, Trevor Darrell, Kate Saenko:
Explainable Neural Computation via Stack Neural Module Networks. CoRR abs/1807.08556 (2018) - [i47]Ulrich Viereck, Kate Saenko, Robert Platt Jr.:
Adapting control policies from simulation to reality using a pairwise loss. CoRR abs/1807.10413 (2018) - [i46]Anna Rohrbach, Lisa Anne Hendricks, Kaylee Burns, Trevor Darrell, Kate Saenko:
Object Hallucination in Image Captioning. CoRR abs/1809.02156 (2018) - [i45]Vasili Ramanishka, Yi-Ting Chen, Teruhisa Misu, Kate Saenko:
Toward Driving Scene Understanding: A Dataset for Learning Driver Behavior and Causal Reasoning. CoRR abs/1811.02307 (2018) - [i44]Bryan A. Plummer, Kevin J. Shih, Yichen Li, Ke Xu, Svetlana Lazebnik, Stan Sclaroff, Kate Saenko:
Open-vocabulary Phrase Detection. CoRR abs/1811.07212 (2018) - [i43]Eric Tzeng, Kaylee Burns, Kate Saenko, Trevor Darrell:
SPLAT: Semantic Pixel-Level Adaptation Transforms for Detection. CoRR abs/1812.00929 (2018) - [i42]Ximeng Sun, Huijuan Xu, Kate Saenko:
A Two-Stream Variational Adversarial Network for Video Generation. CoRR abs/1812.01037 (2018) - [i41]Xingchao Peng, Qinxun Bai, Xide Xia, Zijun Huang, Kate Saenko, Bo Wang:
Moment Matching for Multi-Source Domain Adaptation. CoRR abs/1812.01754 (2018) - [i40]Sarah Adel Bargal, Andrea Zunino, Vitali Petsiuk, Jianming Zhang, Kate Saenko, Vittorio Murino, Stan Sclaroff:
Guided Zoom: Questioning Network Evidence for Fine-grained Classification. CoRR abs/1812.02626 (2018) - [i39]Kuniaki Saito, Yoshitaka Ushiku, Tatsuya Harada, Kate Saenko:
Strong-Weak Distribution Alignment for Adaptive Object Detection. CoRR abs/1812.04798 (2018) - [i38]Huijuan Xu, Bingyi Kang, Ximeng Sun, Jiashi Feng, Kate Saenko, Trevor Darrell:
Similarity R-C3D for Few-shot Temporal Activity Detection. CoRR abs/1812.10000 (2018) - 2017
- [i37]Xingchao Peng, Kate Saenko:
Synthetic to Real Adaptation with Deep Generative Correlation Alignment Networks. CoRR abs/1701.05524 (2017) - [i36]Eric Tzeng, Judy Hoffman, Kate Saenko, Trevor Darrell:
Adversarial Discriminative Domain Adaptation. CoRR abs/1702.05464 (2017) - [i35]Huijuan Xu, Abir Das, Kate Saenko:
R-C3D: Region Convolutional 3D Network for Temporal Activity Detection. CoRR abs/1703.07814 (2017) - [i34]Ronghang Hu, Jacob Andreas, Marcus Rohrbach, Trevor Darrell, Kate Saenko:
Learning to Reason: End-to-End Module Networks for Visual Question Answering. CoRR abs/1704.05526 (2017) - [i33]Ulrich Viereck, Andreas ten Pas, Kate Saenko, Robert Platt Jr.:
Learning a visuomotor controller for real world robotic grasping using easily simulated depth images. CoRR abs/1706.04652 (2017) - [i32]Andreas ten Pas, Marcus Gualtieri, Kate Saenko, Robert Platt Jr.:
Grasp Pose Detection in Point Clouds. CoRR abs/1706.09911 (2017) - [i31]Ben Usman, Kate Saenko, Brian Kulis:
Stable Distribution Alignment Using the Dual of the Adversarial Distance. CoRR abs/1707.04046 (2017) - [i30]Xingchao Peng, Ben Usman, Neela Kaushik, Judy Hoffman, Dequan Wang, Kate Saenko:
VisDA: The Visual Domain Adaptation Challenge. CoRR abs/1710.06924 (2017) - [i29]Kuniaki Saito, Yoshitaka Ushiku, Tatsuya Harada, Kate Saenko:
Adversarial Dropout Regularization. CoRR abs/1711.01575 (2017) - [i28]Judy Hoffman, Eric Tzeng, Taesung Park, Jun-Yan Zhu, Phillip Isola, Kate Saenko, Alexei A. Efros, Trevor Darrell:
CyCADA: Cycle-Consistent Adversarial Domain Adaptation. CoRR abs/1711.03213 (2017) - [i27]Andrew Levy, Robert Platt Jr., Kate Saenko:
Hierarchical Actor-Critic. CoRR abs/1712.00948 (2017) - 2016
- [i26]Marcus Gualtieri, Andreas ten Pas, Kate Saenko, Robert Platt Jr.:
High precision grasp pose detection in dense clutter. CoRR abs/1603.01564 (2016) - [i25]Subhashini Venugopalan, Lisa Anne Hendricks, Raymond J. Mooney, Kate Saenko:
Improving LSTM-based Video Description with Linguistic Knowledge Mined from Text. CoRR abs/1604.01729 (2016) - [i24]Xingchao Peng, Judy Hoffman, Stella X. Yu, Kate Saenko:
Fine-to-coarse Knowledge Transfer For Low-Res Image Classification. CoRR abs/1605.06695 (2016) - [i23]Subhashini Venugopalan, Lisa Anne Hendricks, Marcus Rohrbach, Raymond J. Mooney, Trevor Darrell, Kate Saenko:
Captioning Images with Diverse Objects. CoRR abs/1606.07770 (2016) - [i22]Baochen Sun, Kate Saenko:
Deep CORAL: Correlation Alignment for Deep Domain Adaptation. CoRR abs/1607.01719 (2016) - [i21]Xingchao Peng, Kate Saenko:
Combining Texture and Shape Cues for Object Recognition With Minimal Supervision. CoRR abs/1609.04356 (2016) - [i20]Ronghang Hu, Marcus Rohrbach, Jacob Andreas, Trevor Darrell, Kate Saenko:
Modeling Relationships in Referential Expressions with Compositional Modular Networks. CoRR abs/1611.09978 (2016) - [i19]Baochen Sun, Jiashi Feng, Kate Saenko:
Correlation Alignment for Unsupervised Domain Adaptation. CoRR abs/1612.01939 (2016) - [i18]Vasili Ramanishka, Abir Das, Jianming Zhang, Kate Saenko:
Top-down Visual Saliency Guided by Captions. CoRR abs/1612.07360 (2016) - 2015
- [i17]Subhashini Venugopalan, Marcus Rohrbach, Jeff Donahue, Raymond J. Mooney, Trevor Darrell, Kate Saenko:
Sequence to Sequence - Video to Text. CoRR abs/1505.00487 (2015) - [i16]Huijuan Xu, Subhashini Venugopalan, Vasili Ramanishka, Marcus Rohrbach, Kate Saenko:
A Multi-scale Multiple Instance Video Description Network. CoRR abs/1505.05914 (2015) - [i15]Eric Tzeng, Judy Hoffman, Trevor Darrell, Kate Saenko:
Simultaneous Deep Transfer Across Domains and Tasks. CoRR abs/1510.02192 (2015) - [i14]Damian Mrowca, Marcus Rohrbach, Judy Hoffman, Ronghang Hu, Kate Saenko, Trevor Darrell:
Spatial Semantic Regularisation for Large Scale Object Detection. CoRR abs/1510.02949 (2015) - [i13]Ronghang Hu, Huazhe Xu, Marcus Rohrbach, Jiashi Feng, Kate Saenko, Trevor Darrell:
Natural Language Object Retrieval. CoRR abs/1511.04164 (2015) - [i12]Huijuan Xu, Kate Saenko:
Ask, Attend and Answer: Exploring Question-Guided Spatial Attention for Visual Question Answering. CoRR abs/1511.05234 (2015) - [i11]Lisa Anne Hendricks, Subhashini Venugopalan, Marcus Rohrbach, Raymond J. Mooney, Kate Saenko, Trevor Darrell:
Deep Compositional Captioning: Describing Novel Object Categories without Paired Training Data. CoRR abs/1511.05284 (2015) - [i10]Baochen Sun, Jiashi Feng, Kate Saenko:
Return of Frustratingly Easy Domain Adaptation. CoRR abs/1511.05547 (2015) - [i9]Eric Tzeng, Coline Devin, Judy Hoffman, Chelsea Finn, Xingchao Peng, Sergey Levine, Kate Saenko, Trevor Darrell:
Towards Adapting Deep Visuomotor Representations from Simulated to Real Environments. CoRR abs/1511.07111 (2015) - 2014
- [i8]Judy Hoffman, Sergio Guadarrama, Eric Tzeng, Jeff Donahue, Ross B. Girshick, Trevor Darrell, Kate Saenko:
LSDA: Large Scale Detection Through Adaptation. CoRR abs/1407.5035 (2014) - [i7]Jeff Donahue, Lisa Anne Hendricks, Sergio Guadarrama, Marcus Rohrbach, Subhashini Venugopalan, Kate Saenko, Trevor Darrell:
Long-term Recurrent Convolutional Networks for Visual Recognition and Description. CoRR abs/1411.4389 (2014) - [i6]Judy Hoffman, Deepak Pathak, Trevor Darrell, Kate Saenko:
Detector Discovery in the Wild: Joint Multiple Instance and Representation Learning. CoRR abs/1412.1135 (2014) - [i5]Eric Tzeng, Judy Hoffman, Ning Zhang, Kate Saenko, Trevor Darrell:
Deep Domain Confusion: Maximizing for Domain Invariance. CoRR abs/1412.3474 (2014) - [i4]Subhashini Venugopalan, Huijuan Xu, Jeff Donahue, Marcus Rohrbach, Raymond J. Mooney, Kate Saenko:
Translating Videos to Natural Language Using Deep Recurrent Neural Networks. CoRR abs/1412.4729 (2014) - [i3]Xingchao Peng, Baochen Sun, Karim Ali, Kate Saenko:
Exploring Invariances in Deep Convolutional Neural Networks Using Synthetic Images. CoRR abs/1412.7122 (2014) - 2013
- [i2]Erik Rodner, Judy Hoffman, Jeff Donahue, Trevor Darrell, Kate Saenko:
Towards Adapting ImageNet to Reality: Scalable Domain Adaptation with Implicit Low-rank Transformations. CoRR abs/1308.4200 (2013) - [i1]Ayan Chakrabarti, Ying Xiong, Baochen Sun, Trevor Darrell, Daniel Scharstein, Todd E. Zickler, Kate Saenko:
Modeling Radiometric Uncertainty for Vision with Tone-mapped Color Images. CoRR abs/1311.6887 (2013)
Coauthor Index
aka: Sarah A. Bargal
aka: Jeffrey Donahue
aka: Rogério Schmidt Feris
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