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2020 – today
- 2024
[j9]Han-Jia Ye
, Lu Ming, De-Chuan Zhan, Wei-Lun Chao:
Few-Shot Learning With a Strong Teacher. IEEE Trans. Pattern Anal. Mach. Intell. 46(3): 1425-1440 (2024)- [j8]Jinxuan Xu, Hong-You Chen, Wei-Lun Chao, Yuqian Zhang:
Jigsaw Game: Federated Clustering. Trans. Mach. Learn. Res. 2024 (2024) - [c64]Vardaan Pahuja, Weidi Luo, Yu Gu, Cheng-Hao Tu, Hong-You Chen, Tanya Y. Berger-Wolf, Charles V. Stewart, Song Gao, Wei-Lun Chao, Yu Su:
Reviving the Context: Camera Trap Species Classification as Link Prediction on Multimodal Knowledge Graphs. CIKM 2024: 1825-1835 - [c63]Jihyung Kil, Chan Hee Song, Boyuan Zheng, Xiang Deng, Yu Su, Wei-Lun Chao:
Dual-View Visual Contextualization for Web Navigation. CVPR 2024: 14445-14454 - [c62]Samuel Stevens, Jiaman Wu, Matthew J. Thompson, Elizabeth G. Campolongo, Chan Hee Song, David Edward Carlyn, Li Dong, Wasila M. Dahdul, Charles V. Stewart, Tanya Y. Berger-Wolf, Wei-Lun Chao, Yu Su:
BioCLIP: A Vision Foundation Model for the Tree of Life. CVPR 2024: 19412-19424 - [c61]Tai-Yu Pan, Chenyang Ma, Tianle Chen, Cheng Perng Phoo, Katie Z. Luo, Yurong You, Mark Campbell, Kilian Q. Weinberger, Bharath Hariharan, Wei-Lun Chao:
Pre-training LiDAR-based 3D Object Detectors through Colorization. ICLR 2024 - [c60]Dipanjyoti Paul, Arpita Chowdhury, Xinqi Xiong, Feng-Ju Chang, David Edward Carlyn, Samuel Stevens, Kaiya Provost, Anuj Karpatne, Bryan Carstens, Daniel I. Rubenstein, Charles V. Stewart, Tanya Y. Berger-Wolf, Yu Su, Wei-Lun Chao:
A Simple Interpretable Transformer for Fine-Grained Image Classification and Analysis. ICLR 2024 - [c59]Yurong You, Cheng Perng Phoo, Carlos Andres Diaz-Ruiz, Katie Z. Luo, Wei-Lun Chao, Mark E. Campbell, Bharath Hariharan, Kilian Q. Weinberger:
Better Monocular 3D Detectors with LiDAR from the Past. ICRA 2024: 6634-6641 - [i78]Vardaan Pahuja, Weidi Luo, Yu Gu, Cheng-Hao Tu, Hong-You Chen, Tanya Y. Berger-Wolf, Charles V. Stewart, Song Gao, Wei-Lun Chao, Yu Su:
Bringing Back the Context: Camera Trap Species Identification as Link Prediction on Multimodal Knowledge Graphs. CoRR abs/2401.00608 (2024) - [i77]Jihyung Kil, Chan Hee Song, Boyuan Zheng, Xiang Deng, Yu Su, Wei-Lun Chao:
Dual-View Visual Contextualization for Web Navigation. CoRR abs/2402.04476 (2024) - [i76]Yurong You, Cheng Perng Phoo, Carlos Andres Diaz-Ruiz, Katie Z. Luo, Wei-Lun Chao, Mark E. Campbell, Bharath Hariharan, Kilian Q. Weinberger:
Better Monocular 3D Detectors with LiDAR from the Past. CoRR abs/2404.05139 (2024) - [i75]Xiangyu Chen, Zhenzhen Liu, Katie Z. Luo, Siddhartha Datta, Adhitya Polavaram, Yan Wang, Yurong You, Boyi Li, Marco Pavone, Wei-Lun Chao, Mark E. Campbell, Bharath Hariharan, Kilian Q. Weinberger:
DiffuBox: Refining 3D Object Detection with Point Diffusion. CoRR abs/2405.16034 (2024) - [i74]Kazi Sajeed Mehrab, M. Maruf, Arka Daw, Harish Babu Manogaran, Abhilash Neog, Mridul Khurana, Bahadir Altintas, Yasin Bakis, Elizabeth G. Campolongo, Matthew J. Thompson, Xiaojun Wang, Hilmar Lapp, Wei-Lun Chao, Paula M. Mabee, Henry L. Bart Jr., Wasila M. Dahdul, Anuj Karpatne:
Fish-Vista: A Multi-Purpose Dataset for Understanding & Identification of Traits from Images. CoRR abs/2407.08027 (2024) - [i73]Jinxuan Xu, Hong-You Chen, Wei-Lun Chao, Yuqian Zhang:
Jigsaw Game: Federated Clustering. CoRR abs/2407.12764 (2024) - [i72]Jihyung Kil, Zheda Mai, Justin Lee, Zihe Wang, Kerrie Cheng, Lemeng Wang, Ye Liu, Arpita Chowdhury, Wei-Lun Chao:
CompBench: A Comparative Reasoning Benchmark for Multimodal LLMs. CoRR abs/2407.16837 (2024) - [i71]Mridul Khurana, Arka Daw, M. Maruf, Josef C. Uyeda, Wasila M. Dahdul, Caleb Charpentier, Yasin Bakis, Henry L. Bart Jr., Paula M. Mabee, Hilmar Lapp, James P. Balhoff, Wei-Lun Chao, Charles V. Stewart, Tanya Y. Berger-Wolf, Anuj Karpatne:
Hierarchical Conditioning of Diffusion Models Using Tree-of-Life for Studying Species Evolution. CoRR abs/2408.00160 (2024) - [i70]M. Maruf, Arka Daw, Kazi Sajeed Mehrab, Harish Babu Manogaran, Abhilash Neog, Medha Sawhney, Mridul Khurana, James P. Balhoff, Yasin Bakis, Bahadir Altintas, Matthew J. Thompson, Elizabeth G. Campolongo, Josef C. Uyeda, Hilmar Lapp, Henry L. Bart Jr., Paula M. Mabee, Yu Su, Wei-Lun Chao, Charles V. Stewart, Tanya Y. Berger-Wolf, Wasila M. Dahdul, Anuj Karpatne:
VLM4Bio: A Benchmark Dataset to Evaluate Pretrained Vision-Language Models for Trait Discovery from Biological Images. CoRR abs/2408.16176 (2024) - [i69]Amin Karimi Monsefi, Mengxi Zhou, Nastaran Karimi Monsefi, Ser-Nam Lim, Wei-Lun Chao, Rajiv Ramnath:
Frequency-Guided Masking for Enhanced Vision Self-Supervised Learning. CoRR abs/2409.10362 (2024) - [i68]Ziwei Li, Xiaoqi Wang, Hong-You Chen, Han-Wei Shen, Wei-Lun Chao:
FedNE: Surrogate-Assisted Federated Neighbor Embedding for Dimensionality Reduction. CoRR abs/2409.11509 (2024) - [i67]Zheda Mai, Arpita Chowdhury, Ping Zhang, Cheng-Hao Tu, Hong-You Chen, Vardaan Pahuja, Tanya Y. Berger-Wolf, Song Gao, Charles V. Stewart, Yu Su, Wei-Lun Chao:
Fine-Tuning is Fine, if Calibrated. CoRR abs/2409.16223 (2024) - [i66]Zheda Mai, Ping Zhang, Cheng-Hao Tu, Hong-You Chen, Li Zhang, Wei-Lun Chao:
Lessons Learned from a Unifying Empirical Study of Parameter-Efficient Transfer Learning (PETL) in Visual Recognition. CoRR abs/2409.16434 (2024) - [i65]Pouyan Navard, Amin Karimi Monsefi, Mengxi Zhou, Wei-Lun Chao, Alper Yilmaz, Rajiv Ramnath:
KnobGen: Controlling the Sophistication of Artwork in Sketch-Based Diffusion Models. CoRR abs/2410.01595 (2024) - [i64]Jinsu Yoo, Zhenyang Feng, Tai-Yu Pan, Yihong Sun, Cheng Perng Phoo, Xiangyu Chen, Mark E. Campbell, Kilian Q. Weinberger, Bharath Hariharan, Wei-Lun Chao:
Learning 3D Perception from Others' Predictions. CoRR abs/2410.02646 (2024) - 2023
- [j7]Ziwei Li, Jiayi Xu, Wei-Lun Chao, Han-Wei Shen:
Visual Analytics on Network Forgetting for Task-Incremental Learning. Comput. Graph. Forum 42(3): 437-448 (2023) - [c58]Cheng-Hao Tu, Hong-You Chen, David Carlyn, Wei-Lun Chao:
Learning Fractals by Gradient Descent. AAAI 2023: 2456-2464 - [c57]Cheng-Hao Tu, Zheda Mai, Wei-Lun Chao:
Visual Query Tuning: Towards Effective Usage of Intermediate Representations for Parameter and Memory Efficient Transfer Learning. CVPR 2023: 7725-7735 - [c56]Hong-You Chen, Yandong Li, Yin Cui, Mingda Zhang, Wei-Lun Chao, Li Zhang:
Train-Once-for-All Personalization. CVPR 2023: 11818-11827 - [c55]Tai-Yu Pan, Qing Liu, Wei-Lun Chao, Brian L. Price:
Towards Open-World Segmentation of Parts. CVPR 2023: 15392-15401 - [c54]Yuxiao Qu, Jinmeng Rao, Song Gao, Qianheng Zhang, Wei-Lun Chao, Yu Su, Michelle Miller, Alfonso Morales, Patrick R. Huber:
FLEE-GNN: A Federated Learning System for Edge-Enhanced Graph Neural Network in Analyzing Geospatial Resilience of Multicommodity Food Flows. GeoAI@SIGSPATIAL 2023: 63-72 - [c53]Reza Averly, Wei-Lun Chao:
Unified Out-Of-Distribution Detection: A Model-Specific Perspective. ICCV 2023: 1453-1463 - [c52]Chan Hee Song, Brian M. Sadler, Jiaman Wu, Wei-Lun Chao, Clayton Washington, Yu Su:
LLM-Planner: Few-Shot Grounded Planning for Embodied Agents with Large Language Models. ICCV 2023: 2986-2997 - [c51]Jihyung Kil, Soravit Changpinyo, Xi Chen, Hexiang Hu, Sebastian Goodman, Wei-Lun Chao, Radu Soricut:
PreSTU: Pre-Training for Scene-Text Understanding. ICCV 2023: 15224-15234 - [c50]Travis Zhang, Katie Luo, Cheng Perng Phoo, Yurong You, Wei-Lun Chao, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger:
Unsupervised Domain Adaptation for Self-Driving from Past Traversal Features. ICCV (Workshops) 2023: 4042-4048 - [c49]Hong-You Chen, Cheng-Hao Tu, Ziwei Li, Han-Wei Shen, Wei-Lun Chao:
On the Importance and Applicability of Pre-Training for Federated Learning. ICLR 2023 - [c48]Junan Chen, Josephine Monica, Wei-Lun Chao, Mark E. Campbell:
Probabilistic Uncertainty Quantification of Prediction Models with Application to Visual Localization. ICRA 2023: 4178-4184 - [c47]Youya Xia, Josephine Monica, Wei-Lun Chao, Bharath Hariharan, Kilian Q. Weinberger, Mark E. Campbell:
Image-to-Image Translation for Autonomous Driving from Coarsely-Aligned Image Pairs. ICRA 2023: 7756-7762 - [c46]Mohannad Elhamod, Mridul Khurana, Harish Babu Manogaran, Josef C. Uyeda, Meghan A. Balk, Wasila M. Dahdul, Yasin Bakis, Henry L. Bart Jr., Paula M. Mabee, Hilmar Lapp, James P. Balhoff, Caleb Charpentier, David Carlyn, Wei-Lun Chao, Charles V. Stewart, Daniel I. Rubenstein, Tanya Y. Berger-Wolf, Anuj Karpatne:
Discovering Novel Biological Traits From Images Using Phylogeny-Guided Neural Networks. KDD 2023: 3966-3978 - [c45]Cheng-Hao Tu, Hong-You Chen, Zheda Mai, Jike Zhong, Vardaan Pahuja, Tanya Y. Berger-Wolf, Song Gao, Charles V. Stewart, Yu Su, Wei-Lun Chao:
Holistic Transfer: Towards Non-Disruptive Fine-Tuning with Partial Target Data. NeurIPS 2023 - [i63]Jike Zhong, Hong-You Chen, Wei-Lun Chao:
Making Batch Normalization Great in Federated Deep Learning. CoRR abs/2303.06530 (2023) - [i62]Cheng-Hao Tu, Hong-You Chen, David Carlyn, Wei-Lun Chao:
Learning Fractals by Gradient Descent. CoRR abs/2303.12722 (2023) - [i61]Yurong You, Cheng Perng Phoo, Katie Z. Luo, Travis Zhang, Wei-Lun Chao, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger:
Unsupervised Adaptation from Repeated Traversals for Autonomous Driving. CoRR abs/2303.15286 (2023) - [i60]Reza Averly, Wei-Lun Chao:
Unified Out-Of-Distribution Detection: A Model-Specific Perspective. CoRR abs/2304.06813 (2023) - [i59]Hong-You Chen, Jike Zhong, Mingda Zhang, Xuhui Jia, Hang Qi, Boqing Gong, Wei-Lun Chao, Li Zhang:
Federated Learning of Shareable Bases for Personalization-Friendly Image Classification. CoRR abs/2304.07882 (2023) - [i58]Tianle Chen, Zheda Mai, Ruiwen Li, Wei-Lun Chao:
Segment Anything Model (SAM) Enhanced Pseudo Labels for Weakly Supervised Semantic Segmentation. CoRR abs/2305.05803 (2023) - [i57]Tai-Yu Pan, Qing Liu, Wei-Lun Chao, Brian L. Price:
Towards Open-World Segmentation of Parts. CoRR abs/2305.16804 (2023) - [i56]Junan Chen, Josephine Monica, Wei-Lun Chao, Mark E. Campbell:
Probabilistic Uncertainty Quantification of Prediction Models with Application to Visual Localization. CoRR abs/2305.20044 (2023) - [i55]Mohannad Elhamod, Mridul Khurana, Harish Babu Manogaran, Josef C. Uyeda, Meghan A. Balk, Wasila M. Dahdul, Yasin Bakis, Henry L. Bart Jr., Paula M. Mabee, Hilmar Lapp, James P. Balhoff, Caleb Charpentier, David Carlyn, Wei-Lun Chao, Charles V. Stewart, Daniel I. Rubenstein, Tanya Y. Berger-Wolf, Anuj Karpatne:
Discovering Novel Biological Traits From Images Using Phylogeny-Guided Neural Networks. CoRR abs/2306.03228 (2023) - [i54]Travis Zhang, Katie Luo, Cheng Perng Phoo, Yurong You, Wei-Lun Chao, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger:
Unsupervised Domain Adaptation for Self-Driving from Past Traversal Features. CoRR abs/2309.12140 (2023) - [i53]Yuxiao Qu, Jinmeng Rao, Song Gao, Qianheng Zhang, Wei-Lun Chao, Yu Su, Michelle Miller, Alfonso Morales, Patrick R. Huber:
FLEE-GNN: A Federated Learning System for Edge-Enhanced Graph Neural Network in Analyzing Geospatial Resilience of Multicommodity Food Flows. CoRR abs/2310.13248 (2023) - [i52]Tai-Yu Pan, Chenyang Ma, Tianle Chen, Cheng Perng Phoo, Katie Z. Luo, Yurong You, Mark E. Campbell, Kilian Q. Weinberger, Bharath Hariharan, Wei-Lun Chao:
Pre-Training LiDAR-Based 3D Object Detectors Through Colorization. CoRR abs/2310.14592 (2023) - [i51]Cheng-Hao Tu, Hong-You Chen, Zheda Mai, Jike Zhong, Vardaan Pahuja, Tanya Y. Berger-Wolf, Song Gao, Charles V. Stewart, Yu Su, Wei-Lun Chao:
Holistic Transfer: Towards Non-Disruptive Fine-Tuning with Partial Target Data. CoRR abs/2311.01420 (2023) - [i50]Dipanjyoti Paul, Arpita Chowdhury, Xinqi Xiong, Feng-Ju Chang, David Carlyn, Samuel Stevens, Kaiya Provost, Anuj Karpatne, Bryan Carstens, Daniel I. Rubenstein, Charles V. Stewart, Tanya Y. Berger-Wolf, Yu Su, Wei-Lun Chao:
A Simple Interpretable Transformer for Fine-Grained Image Classification and Analysis. CoRR abs/2311.04157 (2023) - [i49]Samuel Stevens, Jiaman Wu, Matthew J. Thompson, Elizabeth G. Campolongo, Chan Hee Song, David Edward Carlyn, Li Dong, Wasila M. Dahdul, Charles V. Stewart, Tanya Y. Berger-Wolf, Wei-Lun Chao, Yu Su:
BIOCLIP: A Vision Foundation Model for the Tree of Life. CoRR abs/2311.18803 (2023) - 2022
- [j6]Tai-Hsien Wu, Chunfeng Lian, Sanghee Lee, Matthew Pastewait, Christian Piers, Jie Liu, Fan Wang, Li Wang, Chiung-Ying Chiu, Wenchi Wang, Christina Jackson, Wei-Lun Chao, Dinggang Shen, Ching-Chang Ko:
Two-Stage Mesh Deep Learning for Automated Tooth Segmentation and Landmark Localization on 3D Intraoral Scans. IEEE Trans. Medical Imaging 41(11): 3158-3166 (2022) - [c44]Yurong You, Katie Luo, Cheng Perng Phoo, Wei-Lun Chao, Wen Sun, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger:
Learning to Detect Mobile Objects from LiDAR Scans Without Labels. CVPR 2022: 1120-1130 - [c43]Chan Hee Song, Jihyung Kil, Tai-Yu Pan, Brian M. Sadler, Wei-Lun Chao, Yu Su:
One Step at a Time: Long-Horizon Vision-and-Language Navigation with Milestones. CVPR 2022: 15461-15470 - [c42]Carlos Andres Diaz-Ruiz, Youya Xia, Yurong You, Jose Nino, Junan Chen, Josephine Monica, Xiangyu Chen, Katie Luo, Yan Wang, Marc Emond, Wei-Lun Chao, Bharath Hariharan, Kilian Q. Weinberger, Mark E. Campbell:
Ithaca365: Dataset and Driving Perception under Repeated and Challenging Weather Conditions. CVPR 2022: 21351-21360 - [c41]Cheng Zhang, Tai-Yu Pan, Tianle Chen, Jike Zhong, Wenjin Fu, Wei-Lun Chao:
Learning with Free Object Segments for Long-Tailed Instance Segmentation. ECCV (10) 2022: 655-672 - [c40]Hong-You Chen, Wei-Lun Chao:
On Bridging Generic and Personalized Federated Learning for Image Classification. ICLR 2022 - [c39]Han-Jia Ye, Wei-Lun Chao:
How to Train Your MAML to Excel in Few-Shot Classification. ICLR 2022 - [c38]Yurong You, Katie Z. Luo, Xiangyu Chen, Junan Chen, Wei-Lun Chao, Wen Sun, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger:
Hindsight is 20/20: Leveraging Past Traversals to Aid 3D Perception. ICLR 2022 - [c37]Josephine Monica, Wei-Lun Chao, Mark E. Campbell:
Sequential Joint Shape and Pose Estimation of Vehicles with Application to Automatic Amodal Segmentation Labeling. ICRA 2022: 2678-2685 - [c36]Yurong You, Carlos Andres Diaz-Ruiz, Yan Wang, Wei-Lun Chao, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger:
Exploiting Playbacks in Unsupervised Domain Adaptation for 3D Object Detection in Self-Driving Cars. ICRA 2022: 5070-5077 - [c35]Yurong You, Cheng Perng Phoo, Katie Luo, Travis Zhang, Wei-Lun Chao, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger:
Unsupervised Adaptation from Repeated Traversals for Autonomous Driving. NeurIPS 2022 - [i48]Chan Hee Song, Jihyung Kil, Tai-Yu Pan, Brian M. Sadler, Wei-Lun Chao, Yu Su:
One Step at a Time: Long-Horizon Vision-and-Language Navigation with Milestones. CoRR abs/2202.07028 (2022) - [i47]Cheng Zhang, Tai-Yu Pan, Tianle Chen, Jike Zhong, Wenjin Fu, Wei-Lun Chao:
Learning with Free Object Segments for Long-Tailed Instance Segmentation. CoRR abs/2202.11124 (2022) - [i46]Yurong You, Katie Z. Luo, Xiangyu Chen, Junan Chen, Wei-Lun Chao, Wen Sun, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger:
Hindsight is 20/20: Leveraging Past Traversals to Aid 3D Perception. CoRR abs/2203.11405 (2022) - [i45]Yurong You, Katie Z. Luo, Cheng Perng Phoo, Wei-Lun Chao, Wen Sun, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger:
Learning to Detect Mobile Objects from LiDAR Scans Without Labels. CoRR abs/2203.15882 (2022) - [i44]Hong-You Chen, Cheng-Hao Tu, Ziwei Li, Han-Wei Shen, Wei-Lun Chao:
On Pre-Training for Federated Learning. CoRR abs/2206.11488 (2022) - [i43]Hong-You Chen, Wei-Lun Chao:
Gradual Domain Adaptation without Indexed Intermediate Domains. CoRR abs/2207.04587 (2022) - [i42]Carlos Andres Diaz-Ruiz, Youya Xia, Yurong You, Jose Nino, Junan Chen, Josephine Monica, Xiangyu Chen, Katie Luo, Yan Wang, Marc Emond, Wei-Lun Chao, Bharath Hariharan, Kilian Q. Weinberger, Mark Campbell:
Ithaca365: Dataset and Driving Perception under Repeated and Challenging Weather Conditions. CoRR abs/2208.01166 (2022) - [i41]Jihyung Kil, Soravit Changpinyo, Xi Chen, Hexiang Hu, Sebastian Goodman, Wei-Lun Chao, Radu Soricut:
PreSTU: Pre-Training for Scene-Text Understanding. CoRR abs/2209.05534 (2022) - [i40]Youya Xia, Josephine Monica, Wei-Lun Chao, Bharath Hariharan, Kilian Q. Weinberger, Mark Campbell:
Image-to-Image Translation for Autonomous Driving from Coarsely-Aligned Image Pairs. CoRR abs/2209.11673 (2022) - [i39]Cheng-Hao Tu, Zheda Mai, Wei-Lun Chao:
Visual Query Tuning: Towards Effective Usage of Intermediate Representations for Parameter and Memory Efficient Transfer Learning. CoRR abs/2212.03220 (2022) - [i38]Chan Hee Song, Jiaman Wu, Clayton Washington, Brian M. Sadler, Wei-Lun Chao, Yu Su:
LLM-Planner: Few-Shot Grounded Planning for Embodied Agents with Large Language Models. CoRR abs/2212.04088 (2022) - 2021
- [c34]Jihyung Kil, Cheng Zhang, Dong Xuan, Wei-Lun Chao:
Discovering the Unknown Knowns: Turning Implicit Knowledge in the Dataset into Explicit Training Examples for Visual Question Answering. EMNLP (1) 2021: 6346-6361 - [c33]Han-Jia Ye, De-Chuan Zhan, Wei-Lun Chao:
Procrustean Training for Imbalanced Deep Learning. ICCV 2021: 92-102 - [c32]Cheng Zhang, Tai-Yu Pan, Yandong Li, Hexiang Hu, Dong Xuan, Soravit Changpinyo, Boqing Gong, Wei-Lun Chao:
MosaicOS: A Simple and Effective Use of Object-Centric Images for Long-Tailed Object Detection. ICCV 2021: 407-417 - [c31]Luyu Yang, Yan Wang, Mingfei Gao, Abhinav Shrivastava, Kilian Q. Weinberger, Wei-Lun Chao, Ser-Nam Lim:
Deep Co-Training with Task Decomposition for Semi-Supervised Domain Adaptation. ICCV 2021: 8886-8896 - [c30]Hong-You Chen, Wei-Lun Chao:
FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning. ICLR 2021 - [c29]Jihyung Kil, Wei-Lun Chao:
Revisiting Document Representations for Large-Scale Zero-Shot Learning. NAACL-HLT 2021: 3117-3128 - [c28]Tai-Yu Pan, Cheng Zhang, Yandong Li, Hexiang Hu, Dong Xuan, Soravit Changpinyo, Boqing Gong, Wei-Lun Chao:
On Model Calibration for Long-Tailed Object Detection and Instance Segmentation. NeurIPS 2021: 2529-2542 - [c27]Hong-You Chen, Wei-Lun Chao:
Gradual Domain Adaptation without Indexed Intermediate Domains. NeurIPS 2021: 8201-8214 - [i37]Cheng Zhang, Tai-Yu Pan, Yandong Li, Hexiang Hu, Dong Xuan, Soravit Changpinyo, Boqing Gong, Wei-Lun Chao:
A Simple and Effective Use of Object-Centric Images for Long-Tailed Object Detection. CoRR abs/2102.08884 (2021) - [i36]Yurong You, Carlos Andres Diaz-Ruiz, Yan Wang, Wei-Lun Chao, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger:
Exploiting Playbacks in Unsupervised Domain Adaptation for 3D Object Detection. CoRR abs/2103.14198 (2021) - [i35]Han-Jia Ye, De-Chuan Zhan, Wei-Lun Chao:
Procrustean Training for Imbalanced Deep Learning. CoRR abs/2104.01769 (2021) - [i34]Jihyung Kil, Wei-Lun Chao:
Revisiting Document Representations for Large-Scale Zero-Shot Learning. CoRR abs/2104.10355 (2021) - [i33]Han-Jia Ye, Wei-Lun Chao:
How to Train Your MAML to Excel in Few-Shot Classification. CoRR abs/2106.16245 (2021) - [i32]Han-Jia Ye, Lu Ming, De-Chuan Zhan, Wei-Lun Chao:
Few-Shot Learning with a Strong Teacher. CoRR abs/2107.00197 (2021) - [i31]Hong-You Chen, Wei-Lun Chao:
On Bridging Generic and Personalized Federated Learning. CoRR abs/2107.00778 (2021) - [i30]Tai-Yu Pan, Cheng Zhang, Yandong Li, Hexiang Hu, Dong Xuan, Soravit Changpinyo, Boqing Gong, Wei-Lun Chao:
On Model Calibration for Long-Tailed Object Detection and Instance Segmentation. CoRR abs/2107.02170 (2021) - [i29]Jihyung Kil, Cheng Zhang, Dong Xuan, Wei-Lun Chao:
Discovering the Unknown Knowns: Turning Implicit Knowledge in the Dataset into Explicit Training Examples for Visual Question Answering. CoRR abs/2109.06122 (2021) - [i28]Josephine Monica, Wei-Lun Chao, Mark E. Campbell:
Sequential Joint Shape and Pose Estimation of Vehicles with Application to Automatic Amodal Segmentation Labeling. CoRR abs/2109.09840 (2021) - [i27]Tai-Hsien Wu, Chunfeng Lian, Sanghee Lee, Matthew Pastewait, Christian Piers, Jie Liu, Fang Wang, Li Wang, Christina Jackson, Wei-Lun Chao, Dinggang Shen, Ching-Chang Ko:
Two-Stage Mesh Deep Learning for Automated Tooth Segmentation and Landmark Localization on 3D Intraoral Scans. CoRR abs/2109.11941 (2021) - 2020
- [j5]Soravit Changpinyo, Wei-Lun Chao, Boqing Gong, Fei Sha:
Classifier and Exemplar Synthesis for Zero-Shot Learning. Int. J. Comput. Vis. 128(1): 166-201 (2020) - [j4]Vikram Shree, Wei-Lun Chao, Mark Campbell:
Interactive Natural Language-Based Person Search. IEEE Robotics Autom. Lett. 5(2): 1851-1858 (2020) - [c26]Rui Qian, Divyansh Garg, Yan Wang, Yurong You, Serge J. Belongie, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger, Wei-Lun Chao:
End-to-End Pseudo-LiDAR for Image-Based 3D Object Detection. CVPR 2020: 5880-5889 - [c25]Yan Wang, Xiangyu Chen, Yurong You, Li Erran Li, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger, Wei-Lun Chao:
Train in Germany, Test in the USA: Making 3D Object Detectors Generalize. CVPR 2020: 11710-11720 - [c24]Yurong You, Yan Wang, Wei-Lun Chao, Divyansh Garg, Geoff Pleiss, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger:
Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving. ICLR 2020 - [c23]Divyansh Garg, Yan Wang, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger, Wei-Lun Chao:
Wasserstein Distances for Stereo Disparity Estimation. NeurIPS 2020 - [c22]Shih-Han Chou, Wei-Lun Chao, Wei-Sheng Lai, Min Sun, Ming-Hsuan Yang:
Visual Question Answering on 360° Images. WACV 2020: 1596-1605 - [i26]Han-Jia Ye, Hong-You Chen, De-Chuan Zhan, Wei-Lun Chao:
Identifying and Compensating for Feature Deviation in Imbalanced Deep Learning. CoRR abs/2001.01385 (2020) - [i25]Shih-Han Chou, Wei-Lun Chao, Wei-Sheng Lai, Min Sun, Ming-Hsuan Yang:
Visual Question Answering on 360° Images. CoRR abs/2001.03339 (2020) - [i24]Wei-Lun Chao, Han-Jia Ye, De-Chuan Zhan, Mark E. Campbell, Kilian Q. Weinberger:
Revisiting Meta-Learning as Supervised Learning. CoRR abs/2002.00573 (2020) - [i23]Vikram Shree, Wei-Lun Chao, Mark E. Campbell:
An Empirical Study of Person Re-Identification with Attributes. CoRR abs/2002.03752 (2020) - [i22]Vikram Shree, Wei-Lun Chao, Mark E. Campbell:
Interactive Natural Language-based Person Search. CoRR abs/2002.08434 (2020) - [i21]Rui Qian, Divyansh Garg, Yan Wang, Yurong You, Serge J. Belongie, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger, Wei-Lun Chao:
End-to-End Pseudo-LiDAR for Image-Based 3D Object Detection. CoRR abs/2004.03080 (2020) - [i20]Yan Wang, Xiangyu Chen, Yurong You, Li Erran Li, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger, Wei-Lun Chao:
Train in Germany, Test in The USA: Making 3D Object Detectors Generalize. CoRR abs/2005.08139 (2020) - [i19]Divyansh Garg, Yan Wang, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger, Wei-Lun Chao:
Wasserstein Distances for Stereo Disparity Estimation. CoRR abs/2007.03085 (2020) - [i18]Luyu Yang, Yan Wang, Mingfei Gao, Abhinav Shrivastava, Kilian Q. Weinberger, Wei-Lun Chao, Ser-Nam Lim:
MiCo: Mixup Co-Training for Semi-Supervised Domain Adaptation. CoRR abs/2007.12684 (2020) - [i17]Hong-You Chen, Wei-Lun Chao:
FedDistill: Making Bayesian Model Ensemble Applicable to Federated Learning. CoRR abs/2009.01974 (2020)
2010 – 2019
- 2019
- [j3]Brian H. Wang, Wei-Lun Chao, Yan Wang, Bharath Hariharan, Kilian Q. Weinberger, Mark Campbell:
LDLS: 3-D Object Segmentation Through Label Diffusion From 2-D Images. IEEE Robotics Autom. Lett. 4(3): 2902-2909 (2019) - [c21]Cheng Zhang, Wei-Lun Chao, Dong Xuan:
An Empirical Study on Leveraging Scene Graphs for Visual Question Answering. BMVC 2019: 288 - [c20]Carlos Diaz-Ruiz, Yan Wang, Wei-Lun Chao, Kilian Q. Weinberger, Mark E. Campbell:
Vision-only 3D Tracking for Self-Driving Cars. CASE 2019: 1029-1034 - [c19]Yan Wang, Wei-Lun Chao, Divyansh Garg, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger:
Pseudo-LiDAR From Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving. CVPR 2019: 8445-8453 - [c18]Shengyuan Hu, Tao Yu, Chuan Guo, Wei-Lun Chao, Kilian Q. Weinberger:
A New Defense Against Adversarial Images: Turning a Weakness into a Strength. NeurIPS 2019: 1633-1644 - [c17]Vikram Shree, Wei-Lun Chao, Mark E. Campbell:
An Empirical Study of Person Re-Identification with Attributes. RO-MAN 2019: 1-8 - [i16]Yurong You, Yan Wang, Wei-Lun Chao, Divyansh Garg, Geoff Pleiss, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger:
Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving. CoRR abs/1906.06310 (2019) - [i15]Cheng Zhang, Wei-Lun Chao, Dong Xuan:
An Empirical Study on Leveraging Scene Graphs for Visual Question Answering. CoRR abs/1907.12133 (2019) - [i14]Tao Yu, Shengyuan Hu, Chuan Guo, Wei-Lun Chao, Kilian Q. Weinberger:
A New Defense Against Adversarial Images: Turning a Weakness into a Strength. CoRR abs/1910.07629 (2019) - [i13]Brian H. Wang, Wei-Lun Chao, Yan Wang, Bharath Hariharan, Kilian Q. Weinberger, Mark E. Campbell:
LDLS: 3-D Object Segmentation Through Label Diffusion From 2-D Images. CoRR abs/1910.13955 (2019) - [i12]Yan Wang, Wei-Lun Chao, Kilian Q. Weinberger, Laurens van der Maaten:
SimpleShot: Revisiting Nearest-Neighbor Classification for Few-Shot Learning. CoRR abs/1911.04623 (2019) - 2018
- [c16]Hexiang Hu, Wei-Lun Chao, Fei Sha:
Learning Answer Embeddings for Visual Question Answering. CVPR 2018: 5428-5436 - [c15]Wei-Lun Chao, Hexiang Hu, Fei Sha:
Cross-Dataset Adaptation for Visual Question Answering. CVPR 2018: 5716-5725 - [c14]Wei-Lun Chao, Hexiang Hu, Fei Sha:
Being Negative but Constructively: Lessons Learnt from Creating Better Visual Question Answering Datasets. NAACL-HLT 2018: 431-441 - [i11]Hexiang Hu, Wei-Lun Chao, Fei Sha:
Learning Answer Embeddings for Visual Question Answering. CoRR abs/1806.03724 (2018) - [i10]Wei-Lun Chao, Hexiang Hu, Fei Sha:
Cross-Dataset Adaptation for Visual Question Answering. CoRR abs/1806.03726 (2018) - [i9]Soravit Changpinyo, Wei-Lun Chao, Boqing Gong, Fei Sha:
Classifier and Exemplar Synthesis for Zero-Shot Learning. CoRR abs/1812.06423 (2018) - [i8]Yan Wang, Wei-Lun Chao, Divyansh Garg, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger:
Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving. CoRR abs/1812.07179 (2018) - 2017
- [c13]Soravit Changpinyo, Wei-Lun Chao, Fei Sha:
Predicting Visual Exemplars of Unseen Classes for Zero-Shot Learning. ICCV 2017: 3496-3505 - [i7]Wei-Lun Chao, Hexiang Hu, Fei Sha:
Being Negative but Constructively: Lessons Learnt from Creating Better Visual Question Answering Datasets. CoRR abs/1704.07121 (2017) - 2016
- [c12]Ke Zhang, Wei-Lun Chao, Fei Sha, Kristen Grauman:
Summary Transfer: Exemplar-Based Subset Selection for Video Summarization. CVPR 2016: 1059-1067 - [c11]Soravit Changpinyo, Wei-Lun Chao, Boqing Gong, Fei Sha:
Synthesized Classifiers for Zero-Shot Learning. CVPR 2016: 5327-5336 - [c10]Wei-Lun Chao, Soravit Changpinyo, Boqing Gong, Fei Sha:
An Empirical Study and Analysis of Generalized Zero-Shot Learning for Object Recognition in the Wild. ECCV (2) 2016: 52-68 - [c9]Ke Zhang, Wei-Lun Chao, Fei Sha, Kristen Grauman:
Video Summarization with Long Short-Term Memory. ECCV (7) 2016: 766-782 - [i6]Soravit Changpinyo, Wei-Lun Chao, Boqing Gong, Fei Sha:
Synthesized Classifiers for Zero-Shot Learning. CoRR abs/1603.00550 (2016) - [i5]Ke Zhang, Wei-Lun Chao, Fei Sha, Kristen Grauman:
Summary Transfer: Exemplar-based Subset Selection for Video Summarization. CoRR abs/1603.03369 (2016) - [i4]Wei-Lun Chao, Soravit Changpinyo, Boqing Gong, Fei Sha:
An Empirical Study and Analysis of Generalized Zero-Shot Learning for Object Recognition in the Wild. CoRR abs/1605.04253 (2016) - [i3]Ke Zhang, Wei-Lun Chao, Fei Sha, Kristen Grauman:
Video Summarization with Long Short-term Memory. CoRR abs/1605.08110 (2016) - [i2]Soravit Changpinyo, Wei-Lun Chao, Fei Sha:
Predicting Visual Exemplars of Unseen Classes for Zero-Shot Learning. CoRR abs/1605.08151 (2016) - 2015
- [j2]Wei-Lun Chao, Jian-Jiun Ding, Jun-Zuo Liu:
Facial expression recognition based on improved local binary pattern and class-regularized locality preserving projection. Signal Process. 117: 1-10 (2015) - [c8]Wei-Lun Chao, Justin Solomon, Dominik L. Michels, Fei Sha:
Exponential Integration for Hamiltonian Monte Carlo. ICML 2015: 1142-1151 - [c7]Wei-Lun Chao, Boqing Gong, Kristen Grauman, Fei Sha:
Large-Margin Determinantal Point Processes. UAI 2015: 191-200 - 2014
- [c6]Boqing Gong, Wei-Lun Chao, Kristen Grauman, Fei Sha:
Diverse Sequential Subset Selection for Supervised Video Summarization. NIPS 2014: 2069-2077 - [i1]Boqing Gong, Wei-Lun Chao, Kristen Grauman, Fei Sha:
Large-Margin Determinantal Point Processes. CoRR abs/1411.1537 (2014) - 2013
- [j1]Wei-Lun Chao, Jun-Zuo Liu, Jian-Jiun Ding:
Facial age estimation based on label-sensitive learning and age-oriented regression. Pattern Recognit. 46(3): 628-641 (2013) - [c5]Wei-Lun Chao, Jun-Zuo Liu, Jian-Jiun Ding, Po-Hung Wu:
Facial expression recognition using expression-specific local binary patterns and layer denoising mechanism. ICICS 2013: 1-5 - 2012
- [c4]Wei-Lun Chao, Jun-Zuo Liu, Jian-Jiun Ding:
Facial age estimation based on label-sensitive learning and age-specific local regression. ICASSP 2012: 1941-1944 - 2011
- [c3]Wei-Lun Chao, Hsiao-Hang Su, Shao-Yi Chien, Winston H. Hsu, Jian-Jiun Ding:
Coarse-to-fine temporal optimization for video retargeting based on seam carving. ICME 2011: 1-6 - [c2]Jian-Jiun Ding, Yu-Hsiang Wang, Lee-Lin Hu, Wei-Lun Chao, Yio-Wha Shau:
Muscle injury determination by image segmentation. VCIP 2011: 1-4 - 2010
- [c1]Jian-Jiun Ding, Wei-Lun Chao, Jiun-De Huang, Cheng-Jin Kuo:
Asymmetric fourier descriptor of non-closed segments. ICIP 2010: 1613-1616
Coauthor Index
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