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ORCIDJia Deng 0001
Person information
- affiliation (PhD 2012): Princeton University, NJ, USA
- affiliation (former): University of Michigan, Ann Arbor, MI, USA
- affiliation (former): Stanford University, Computer Science Department, CA, USA
Other persons with the same name
- Jia Deng — disambiguation page
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2020 – today
- 2024
[c84]Lahav Lipson, Jia Deng:
Multi-Session SLAM with Differentiable Wide-Baseline Pose Optimization. CVPR 2024: 19626-19635- [c83]Alexander Raistrick, Lingjie Mei, Karhan Kayan, David Yan, Yiming Zuo, Beining Han, Hongyu Wen, Meenal Parakh, Stamatis Alexandropoulos, Lahav Lipson, Zeyu Ma, Jia Deng:
Infinigen Indoors: Photorealistic Indoor Scenes using Procedural Generation. CVPR 2024: 21783-21794 - [c82]Yihan Wang, Lahav Lipson, Jia Deng:
SEA-RAFT: Simple, Efficient, Accurate RAFT for Optical Flow. ECCV (7) 2024: 36-54 - [c81]Yiming Zuo
, Jia Deng:
OGNI-DC: Robust Depth Completion with Optimization-Guided Neural Iterations. ECCV (3) 2024: 78-95 - [c80]Lahav Lipson, Zachary Teed, Jia Deng:
Deep Patch Visual SLAM. ECCV (2) 2024: 424-440 - [c79]Hongyu Wen, Erich Liang, Jia Deng:
LayeredFlow: A Real-World Benchmark for Non-Lambertian Multi-layer Optical Flow. ECCV (2) 2024: 477-495 - [c78]Hei Law, Jia Deng:
Label-Free Synthetic Pretraining of Object Detectors. WACV 2024: 935-945 - [i76]Lahav Lipson, Jia Deng:
Multi-Session SLAM with Differentiable Wide-Baseline Pose Optimization. CoRR abs/2404.15263 (2024) - [i75]Yihan Wang, Lahav Lipson, Jia Deng:
SEA-RAFT: Simple, Efficient, Accurate RAFT for Optical Flow. CoRR abs/2405.14793 (2024) - [i74]Yiming Zuo, Jia Deng:
OGNI-DC: Robust Depth Completion with Optimization-Guided Neural Iterations. CoRR abs/2406.11711 (2024) - [i73]Beining Han, Meenal Parakh, Derek Geng, Jack A Defay, Luyang Gan, Jia Deng:
FetchBench: A Simulation Benchmark for Robot Fetching. CoRR abs/2406.11793 (2024) - [i72]Alexander Raistrick, Lingjie Mei, Karhan Kayan, David Yan, Yiming Zuo, Beining Han, Hongyu Wen, Meenal Parakh, Stamatis Alexandropoulos, Lahav Lipson, Zeyu Ma, Jia Deng:
Infinigen Indoors: Photorealistic Indoor Scenes using Procedural Generation. CoRR abs/2406.11824 (2024) - [i71]Lahav Lipson, Zachary Teed, Jia Deng:
Deep Patch Visual SLAM. CoRR abs/2408.01654 (2024) - [i70]Hongyu Wen, Erich Liang, Jia Deng:
LayeredFlow: A Real-World Benchmark for Non-Lambertian Multi-Layer Optical Flow. CoRR abs/2409.05688 (2024) - [i69]Yiming Zuo, Karhan Kayan, Maggie Wang, Kevin Jeon, Jia Deng, Thomas L. Griffiths:
Towards Foundation Models for 3D Vision: How Close Are We? CoRR abs/2410.10799 (2024) - 2023
- [j7]Kaiyu Yang, Jia Deng:
Learning Symbolic Rules for Reasoning in Quasi-Natural Language. Trans. Mach. Learn. Res. 2023 (2023) - [c77]Alexander Raistrick, Lahav Lipson, Zeyu Ma, Lingjie Mei, Mingzhe Wang, Yiming Zuo, Karhan Kayan, Hongyu Wen, Beining Han, Yihan Wang, Alejandro Newell, Hei Law, Ankit Goyal, Kaiyu Yang, Jia Deng:
Infinite Photorealistic Worlds Using Procedural Generation. CVPR 2023: 12630-12641 - [c76]Yiming Zuo, Jia Deng:
View Synthesis with Sculpted Neural Points. ICLR 2023 - [c75]Agrim Gupta, Jiajun Wu, Jia Deng, Fei-Fei Li:
Siamese Masked Autoencoders. NeurIPS 2023 - [c74]Zachary Teed, Lahav Lipson, Jia Deng:
Deep Patch Visual Odometry. NeurIPS 2023 - [i68]Agrim Gupta, Jiajun Wu, Jia Deng, Li Fei-Fei:
Siamese Masked Autoencoders. CoRR abs/2305.14344 (2023) - [i67]Alexander Raistrick, Lahav Lipson, Zeyu Ma, Lingjie Mei, Mingzhe Wang, Yiming Zuo, Karhan Kayan, Hongyu Wen, Beining Han, Yihan Wang, Alejandro Newell, Hei Law, Ankit Goyal, Kaiyu Yang, Jia Deng:
Infinite Photorealistic Worlds using Procedural Generation. CoRR abs/2306.09310 (2023) - [i66]Zeyu Ma, Alexander Raistrick, Lahav Lipson, Jia Deng:
View-Dependent Octree-based Mesh Extraction in Unbounded Scenes for Procedural Synthetic Data. CoRR abs/2312.08364 (2023) - 2022
- [c73]Lahav Lipson, Zachary Teed, Ankit Goyal, Jia Deng:
Coupled Iterative Refinement for 6D Multi-Object Pose Estimation. CVPR 2022: 6718-6727 - [c72]Ankit Goyal, Arsalan Mousavian, Chris Paxton, Yu-Wei Chao, Brian Okorn, Jia Deng, Dieter Fox:
IFOR: Iterative Flow Minimization for Robotic Object Rearrangement. CVPR 2022: 14767-14777 - [c71]Zeyu Ma, Zachary Teed, Jia Deng:
Multiview Stereo with Cascaded Epipolar RAFT. ECCV (31) 2022: 734-750 - [c70]Kaiyu Yang, Jia Deng, Danqi Chen:
Generating Natural Language Proofs with Verifier-Guided Search. EMNLP 2022: 89-105 - [c69]Kaiyu Yang, Jacqueline H. Yau, Li Fei-Fei, Jia Deng, Olga Russakovsky:
A Study of Face Obfuscation in ImageNet. ICML 2022: 25313-25330 - [c68]Ankit Goyal, Alexey Bochkovskiy, Jia Deng, Vladlen Koltun:
Non-deep Networks. NeurIPS 2022 - [i65]Ankit Goyal, Arsalan Mousavian, Chris Paxton, Yu-Wei Chao, Brian Okorn, Jia Deng, Dieter Fox:
IFOR: Iterative Flow Minimization for Robotic Object Rearrangement. CoRR abs/2202.00732 (2022) - [i64]Lahav Lipson, Zachary Teed, Ankit Goyal, Jia Deng:
Coupled Iterative Refinement for 6D Multi-Object Pose Estimation. CoRR abs/2204.12516 (2022) - [i63]Zeyu Ma, Zachary Teed, Jia Deng:
Multiview Stereo with Cascaded Epipolar RAFT. CoRR abs/2205.04502 (2022) - [i62]Yiming Zuo, Jia Deng:
View Synthesis with Sculpted Neural Points. CoRR abs/2205.05869 (2022) - [i61]Kaiyu Yang, Jia Deng, Danqi Chen:
Generating Natural Language Proofs with Verifier-Guided Search. CoRR abs/2205.12443 (2022) - [i60]Hei Law, Jia Deng:
Label-Free Synthetic Pretraining of Object Detectors. CoRR abs/2208.04268 (2022) - [i59]Zachary Teed, Lahav Lipson, Jia Deng:
Deep Patch Visual Odometry. CoRR abs/2208.04726 (2022) - 2021
- [c67]Lahav Lipson, Zachary Teed, Jia Deng:
RAFT-Stereo: Multilevel Recurrent Field Transforms for Stereo Matching. 3DV 2021: 218-227 - [c66]Yu-Wei Chao, Jimei Yang, Weifeng Chen, Jia Deng:
Learning to Sit: Synthesizing Human-Chair Interactions via Hierarchical Control. AAAI 2021: 5887-5895 - [c65]Lanlan Liu, Yuting Zhang, Jia Deng, Stefano Soatto:
Dynamically Grown Generative Adversarial Networks. AAAI 2021: 8680-8687 - [c64]Zachary Teed, Jia Deng:
RAFT-3D: Scene Flow Using Rigid-Motion Embeddings. CVPR 2021: 8375-8384 - [c63]Zachary Teed, Jia Deng:
Tangent Space Backpropagation for 3D Transformation Groups. CVPR 2021: 10338-10347 - [c62]Ankit Goyal, Hei Law, Bowei Liu, Alejandro Newell, Jia Deng:
Revisiting Point Cloud Shape Classification with a Simple and Effective Baseline. ICML 2021: 3809-3820 - [c61]Zachary Teed, Jia Deng:
RAFT: Recurrent All-Pairs Field Transforms for Optical Flow (Extended Abstract). IJCAI 2021: 4839-4843 - [c60]Zachary Teed, Jia Deng:
DROID-SLAM: Deep Visual SLAM for Monocular, Stereo, and RGB-D Cameras. NeurIPS 2021: 16558-16569 - [i58]Kaiyu Yang, Jacqueline Yau, Li Fei-Fei, Jia Deng, Olga Russakovsky:
A Study of Face Obfuscation in ImageNet. CoRR abs/2103.06191 (2021) - [i57]Zachary Teed, Jia Deng:
Tangent Space Backpropagation for 3D Transformation Groups. CoRR abs/2103.12032 (2021) - [i56]Ankit Goyal, Hei Law, Bowei Liu, Alejandro Newell, Jia Deng:
Revisiting Point Cloud Shape Classification with a Simple and Effective Baseline. CoRR abs/2106.05304 (2021) - [i55]Lanlan Liu, Yuting Zhang, Jia Deng, Stefano Soatto:
Dynamically Grown Generative Adversarial Networks. CoRR abs/2106.08505 (2021) - [i54]Zachary Teed, Jia Deng:
DROID-SLAM: Deep Visual SLAM for Monocular, Stereo, and RGB-D Cameras. CoRR abs/2108.10869 (2021) - [i53]Lahav Lipson, Zachary Teed, Jia Deng:
RAFT-Stereo: Multilevel Recurrent Field Transforms for Stereo Matching. CoRR abs/2109.07547 (2021) - [i52]Ankit Goyal, Alexey Bochkovskiy, Jia Deng, Vladlen Koltun:
Non-deep Networks. CoRR abs/2110.07641 (2021) - [i51]Kaiyu Yang, Jia Deng:
Learning Symbolic Rules for Reasoning in Quasi-Natural Language. CoRR abs/2111.12038 (2021) - 2020
- [j6]Hei Law, Jia Deng:
CornerNet: Detecting Objects as Paired Keypoints. Int. J. Comput. Vis. 128(3): 642-656 (2020) - [c59]Hei Law, Yun Teng, Olga Russakovsky, Jia Deng:
CornerNet-Lite: Efficient Keypoint based Object Detection. BMVC 2020 - [c58]Weifeng Chen, Shengyi Qian, David Fan, Noriyuki Kojima, Max Hamilton, Jia Deng:
OASIS: A Large-Scale Dataset for Single Image 3D in the Wild. CVPR 2020: 676-685 - [c57]Dawei Yang, Jia Deng:
Learning to Generate 3D Training Data Through Hybrid Gradient. CVPR 2020: 776-786 - [c56]Alejandro Newell, Jia Deng:
How Useful Is Self-Supervised Pretraining for Visual Tasks? CVPR 2020: 7343-7352 - [c55]Lanlan Liu, Mingzhe Wang, Jia Deng:
A Unified Framework of Surrogate Loss by Refactoring and Interpolation. ECCV (3) 2020: 278-293 - [c54]Zachary Teed, Jia Deng:
RAFT: Recurrent All-Pairs Field Transforms for Optical Flow. ECCV (2) 2020: 402-419 - [c53]Kaiyu Yang, Klint Qinami, Li Fei-Fei, Jia Deng, Olga Russakovsky:
Towards fairer datasets: filtering and balancing the distribution of the people subtree in the ImageNet hierarchy. FAT* 2020: 547-558 - [c52]Zachary Teed, Jia Deng:
DeepV2D: Video to Depth with Differentiable Structure from Motion. ICLR 2020 - [c51]Ankit Goyal, Jia Deng:
PackIt: A Virtual Environment for Geometric Planning. ICML 2020: 3700-3710 - [c50]Santiago Castro, Mahmoud Azab, Jonathan C. Stroud, Cristina Noujaim, Ruoyao Wang, Jia Deng, Rada Mihalcea:
LifeQA: A Real-life Dataset for Video Question Answering. LREC 2020: 4352-4358 - [c49]Ankit Goyal, Kaiyu Yang, Dawei Yang, Jia Deng:
Rel3D: A Minimally Contrastive Benchmark for Grounding Spatial Relations in 3D. NeurIPS 2020 - [c48]Mingzhe Wang, Jia Deng:
Learning to Prove Theorems by Learning to Generate Theorems. NeurIPS 2020 - [c47]Kaiyu Yang, Jia Deng:
Strongly Incremental Constituency Parsing with Graph Neural Networks. NeurIPS 2020 - [c46]Jonathan C. Stroud, David A. Ross, Chen Sun, Jia Deng, Rahul Sukthankar:
D3D: Distilled 3D Networks for Video Action Recognition. WACV 2020: 614-623 - [i50]Mingzhe Wang, Jia Deng:
Learning to Prove Theorems by Learning to Generate Theorems. CoRR abs/2002.07019 (2020) - [i49]Zachary Teed, Jia Deng:
RAFT: Recurrent All-Pairs Field Transforms for Optical Flow. CoRR abs/2003.12039 (2020) - [i48]Alejandro Newell, Jia Deng:
How Useful is Self-Supervised Pretraining for Visual Tasks? CoRR abs/2003.14323 (2020) - [i47]Ankit Goyal, Jia Deng:
PackIt: A Virtual Environment for Geometric Planning. CoRR abs/2007.11121 (2020) - [i46]Weifeng Chen, Shengyi Qian, David Fan, Noriyuki Kojima, Max Hamilton, Jia Deng:
OASIS: A Large-Scale Dataset for Single Image 3D in the Wild. CoRR abs/2007.13215 (2020) - [i45]Lanlan Liu, Mingzhe Wang, Jia Deng:
A Unified Framework of Surrogate Loss by Refactoring and Interpolation. CoRR abs/2007.13870 (2020) - [i44]Jonathan C. Stroud, David A. Ross, Chen Sun, Jia Deng, Rahul Sukthankar, Cordelia Schmid:
Learning Video Representations from Textual Web Supervision. CoRR abs/2007.14937 (2020) - [i43]Kaiyu Yang, Jia Deng:
Strongly Incremental Constituency Parsing with Graph Neural Networks. CoRR abs/2010.14568 (2020) - [i42]Dhruv Batra, Angel X. Chang, Sonia Chernova, Andrew J. Davison, Jia Deng, Vladlen Koltun, Sergey Levine, Jitendra Malik, Igor Mordatch, Roozbeh Mottaghi, Manolis Savva, Hao Su:
Rearrangement: A Challenge for Embodied AI. CoRR abs/2011.01975 (2020) - [i41]Zachary Teed, Jia Deng:
RAFT-3D: Scene Flow using Rigid-Motion Embeddings. CoRR abs/2012.00726 (2020) - [i40]Ankit Goyal, Kaiyu Yang, Dawei Yang, Jia Deng:
Rel3D: A Minimally Contrastive Benchmark for Grounding Spatial Relations in 3D. CoRR abs/2012.01634 (2020)
2010 – 2019
- 2019
- [c45]Oana Ignat, Laura Burdick, Jia Deng, Rada Mihalcea:
Identifying Visible Actions in Lifestyle Vlogs. ACL (1) 2019: 6406-6417 - [c44]Mahmoud Azab, Noriyuki Kojima, Jia Deng, Rada Mihalcea:
Representing Movie Characters in Dialogues. CoNLL 2019: 99-109 - [c43]Weifeng Chen, Shengyi Qian, Jia Deng:
Learning Single-Image Depth From Videos Using Quality Assessment Networks. CVPR 2019: 5604-5613 - [c42]Chaowei Xiao, Dawei Yang, Bo Li, Jia Deng, Mingyan Liu:
MeshAdv: Adversarial Meshes for Visual Recognition. CVPR 2019: 6898-6907 - [c41]Kaiyu Yang, Olga Russakovsky, Jia Deng:
SpatialSense: An Adversarially Crowdsourced Benchmark for Spatial Relation Recognition. ICCV 2019: 2051-2060 - [c40]Lanlan Liu, Michael Muelly, Jia Deng, Tomas Pfister, Li-Jia Li:
Generative Modeling for Small-Data Object Detection. ICCV 2019: 6072-6080 - [c39]Kaiyu Yang, Jia Deng:
Learning to Prove Theorems via Interacting with Proof Assistants. ICML 2019: 6984-6994 - [i39]Laura Burdick, Oana Ignat, Yiming Zhang, Rada Mihalcea, Mingzhe Wang, Steve Wilson, Yumou Wei, Jia Deng:
Building a Flexible Knowledge Graph to Capture Real-World Events. TAC 2019 - [i38]Hei Law, Yun Teng, Olga Russakovsky, Jia Deng:
CornerNet-Lite: Efficient Keypoint Based Object Detection. CoRR abs/1904.08900 (2019) - [i37]Kaiyu Yang, Jia Deng:
Learning to Prove Theorems via Interacting with Proof Assistants. CoRR abs/1905.09381 (2019) - [i36]Oana Ignat, Laura Burdick, Jia Deng, Rada Mihalcea:
Identifying Visible Actions in Lifestyle Vlogs. CoRR abs/1906.04236 (2019) - [i35]Dawei Yang, Jia Deng:
Learning to Generate Synthetic 3D Training Data through Hybrid Gradient. CoRR abs/1907.00267 (2019) - [i34]Noriyuki Kojima, Jia Deng:
To Learn or Not to Learn: Analyzing the Role of Learning for Navigation in Virtual Environments. CoRR abs/1907.11770 (2019) - [i33]Kaiyu Yang, Olga Russakovsky, Jia Deng:
SpatialSense: An Adversarially Crowdsourced Benchmark for Spatial Relation Recognition. CoRR abs/1908.02660 (2019) - [i32]Alejandro Newell, Lu Jiang, Chong Wang, Li-Jia Li, Jia Deng:
Feature Partitioning for Efficient Multi-Task Architectures. CoRR abs/1908.04339 (2019) - [i31]Yu-Wei Chao, Jimei Yang, Weifeng Chen, Jia Deng:
Learning to Sit: Synthesizing Human-Chair Interactions via Hierarchical Control. CoRR abs/1908.07423 (2019) - [i30]Lanlan Liu, Michael Muelly, Jia Deng, Tomas Pfister, Li-Jia Li:
Generative Modeling for Small-Data Object Detection. CoRR abs/1910.07169 (2019) - [i29]Jonathan C. Stroud, Ryan McCaffrey, Rada Mihalcea, Jia Deng, Olga Russakovsky:
Compositional Temporal Visual Grounding of Natural Language Event Descriptions. CoRR abs/1912.02256 (2019) - [i28]Kaiyu Yang, Klint Qinami, Li Fei-Fei, Jia Deng, Olga Russakovsky:
Towards Fairer Datasets: Filtering and Balancing the Distribution of the People Subtree in the ImageNet Hierarchy. CoRR abs/1912.07726 (2019) - 2018
- [c38]Lanlan Liu, Jia Deng:
Dynamic Deep Neural Networks: Optimizing Accuracy-Efficiency Trade-Offs by Selective Execution. AAAI 2018: 3675-3682 - [c37]Ankit Goyal, Jian Wang, Jia Deng:
Think Visually: Question Answering through Virtual Imagery. ACL (1) 2018: 2598-2608 - [c36]Lei Huang, Dawei Yang, Bo Lang, Jia Deng:
Decorrelated Batch Normalization. CVPR 2018: 791-800 - [c35]Yu-Wei Chao, Sudheendra Vijayanarasimhan, Bryan Seybold, David A. Ross, Jia Deng, Rahul Sukthankar:
Rethinking the Faster R-CNN Architecture for Temporal Action Localization. CVPR 2018: 1130-1139 - [c34]Dawei Yang, Jia Deng:
Shape From Shading Through Shape Evolution. CVPR 2018: 3781-3790 - [c33]Hei Law, Jia Deng:
CornerNet: Detecting Objects as Paired Keypoints. ECCV (14) 2018: 765-781 - [c32]Mahmoud Azab, Mingzhe Wang, Max Smith, Noriyuki Kojima, Jia Deng, Rada Mihalcea:
Speaker Naming in Movies. NAACL-HLT 2018: 2206-2216 - [c31]Yu-Wei Chao, Yunfan Liu, Xieyang Liu, Huayi Zeng, Jia Deng:
Learning to Detect Human-Object Interactions. WACV 2018: 381-389 - [i27]Laura Wendlandt, Steven R. Wilson, Oana Ignat, Charles Welch, Li Zhang, Mingzhe Wang, Jia Deng, Rada Mihalcea:
Entity and Event Extraction from Scratch Using Minimal Training Data. TAC 2018 - [i26]Yu-Wei Chao, Sudheendra Vijayanarasimhan, Bryan Seybold, David A. Ross, Jia Deng, Rahul Sukthankar:
Rethinking the Faster R-CNN Architecture for Temporal Action Localization. CoRR abs/1804.07667 (2018) - [i25]Lei Huang, Dawei Yang, Bo Lang, Jia Deng:
Decorrelated Batch Normalization. CoRR abs/1804.08450 (2018) - [i24]Ankit Goyal, Jian Wang, Jia Deng:
Think Visually: Question Answering through Virtual Imagery. CoRR abs/1805.11025 (2018) - [i23]Weifeng Chen, Jia Deng:
Learning Single-Image Depth from Videos using Quality Assessment Networks. CoRR abs/1806.09573 (2018) - [i22]Hei Law, Jia Deng:
CornerNet: Detecting Objects as Paired Keypoints. CoRR abs/1808.01244 (2018) - [i21]Parker Hill, Babak Zamirai, Shengshuo Lu, Yu-Wei Chao, Michael Laurenzano, Mehrzad Samadi, Marios C. Papaefthymiou, Scott A. Mahlke, Thomas F. Wenisch, Jia Deng, Lingjia Tang, Jason Mars:
Rethinking Numerical Representations for Deep Neural Networks. CoRR abs/1808.02513 (2018) - [i20]Mahmoud Azab, Mingzhe Wang, Max Smith, Noriyuki Kojima, Jia Deng, Rada Mihalcea:
Speaker Naming in Movies. CoRR abs/1809.08761 (2018) - [i19]Dawei Yang, Chaowei Xiao, Bo Li, Jia Deng, Mingyan Liu:
Realistic Adversarial Examples in 3D Meshes. CoRR abs/1810.05206 (2018) - [i18]Zachary Teed, Jia Deng:
DeepV2D: Video to Depth with Differentiable Structure from Motion. CoRR abs/1812.04605 (2018) - [i17]Jonathan C. Stroud, David A. Ross, Chen Sun, Jia Deng, Rahul Sukthankar:
D3D: Distilled 3D Networks for Video Action Recognition. CoRR abs/1812.08249 (2018) - 2017
- [j5]Timnit Gebru, Jonathan Krause, Yilun Wang, Duyun Chen, Jia Deng, Erez Lieberman Aiden, Li Fei-Fei:
Using deep learning and Google Street View to estimate the demographic makeup of neighborhoods across the United States. Proc. Natl. Acad. Sci. USA 114(50): 13108-13113 (2017) - [c30]Timnit Gebru, Jonathan Krause, Yilun Wang, Duyun Chen, Jia Deng, Li Fei-Fei:
Fine-Grained Car Detection for Visual Census Estimation. AAAI 2017: 4502-4508 - [c29]Timnit Gebru, Jonathan Krause, Jia Deng, Li Fei-Fei:
Scalable Annotation of Fine-Grained Categories Without Experts. CHI 2017: 1877-1881 - [c28]Ze-Huan Yuan, Jonathan C. Stroud, Tong Lu, Jia Deng:
Temporal Action Localization by Structured Maximal Sums. CVPR 2017: 3215-3223 - [c27]Yu-Wei Chao, Jimei Yang, Brian L. Price, Scott Cohen, Jia Deng:
Forecasting Human Dynamics from Static Images. CVPR 2017: 3643-3651 - [c26]Weifeng Chen, Donglai Xiang, Jia Deng:
Surface Normals in the Wild. ICCV 2017: 1566-1575 - [c25]Hei Law, Khurshid Ghani, Jia Deng:
Surgeon Technical Skill Assessment using Computer Vision based Analysis. MLHC 2017: 88-99 - [c24]Alejandro Newell, Jia Deng:
Pixels to Graphs by Associative Embedding. NIPS 2017: 2171-2180 - [c23]Alejandro Newell, Zhiao Huang, Jia Deng:
Associative Embedding: End-to-End Learning for Joint Detection and Grouping. NIPS 2017: 2277-2287 - [c22]Mingzhe Wang, Yihe Tang, Jian Wang, Jia Deng:
Premise Selection for Theorem Proving by Deep Graph Embedding. NIPS 2017: 2786-2796 - [i16]Lanlan Liu, Jia Deng:
Dynamic Deep Neural Networks: Optimizing Accuracy-Efficiency Trade-offs by Selective Execution. CoRR abs/1701.00299 (2017) - [i15]Yu-Wei Chao, Yunfan Liu, Xieyang Liu, Huayi Zeng, Jia Deng:
Learning to Detect Human-Object Interactions. CoRR abs/1702.05448 (2017) - [i14]Timnit Gebru, Jonathan Krause, Yilun Wang, Duyun Chen, Jia Deng, Erez Aiden Lieberman, Li Fei-Fei:
Using Deep Learning and Google Street View to Estimate the Demographic Makeup of the US. CoRR abs/1702.06683 (2017) - [i13]Weifeng Chen, Donglai Xiang, Jia Deng:
Surface Normals in the Wild. CoRR abs/1704.02956 (2017) - [i12]Yu-Wei Chao, Jimei Yang, Brian L. Price, Scott Cohen, Jia Deng:
Forecasting Human Dynamics from Static Images. CoRR abs/1704.03432 (2017) - [i11]Ze-Huan Yuan, Jonathan C. Stroud, Tong Lu, Jia Deng:
Temporal Action Localization by Structured Maximal Sums. CoRR abs/1704.04671 (2017) - [i10]Alejandro Newell, Jia Deng:
Pixels to Graphs by Associative Embedding. CoRR abs/1706.07365 (2017) - [i9]Timnit Gebru, Jonathan Krause, Yilun Wang, Duyun Chen, Jia Deng, Li Fei-Fei:
Fine-Grained Car Detection for Visual Census Estimation. CoRR abs/1709.02480 (2017) - [i8]Timnit Gebru, Jonathan Krause, Jia Deng, Li Fei-Fei:
Scalable Annotation of Fine-Grained Categories Without Experts. CoRR abs/1709.02482 (2017) - [i7]Mingzhe Wang, Yihe Tang, Jian Wang, Jia Deng:
Premise Selection for Theorem Proving by Deep Graph Embedding. CoRR abs/1709.09994 (2017) - [i6]Dawei Yang, Jia Deng:
Shape from Shading through Shape Evolution. CoRR abs/1712.02961 (2017) - 2016
- [j4]Vicente Ordonez, Wei Liu, Jia Deng, Yejin Choi, Alexander C. Berg, Tamara L. Berg:
Learning to name objects. Commun. ACM 59(3): 108-115 (2016) - [j3]Jia Deng, Jonathan Krause, Michael Stark, Li Fei-Fei:
Leveraging the Wisdom of the Crowd for Fine-Grained Recognition. IEEE Trans. Pattern Anal. Mach. Intell. 38(4): 666-676 (2016) - [c21]Alejandro Newell, Kaiyu Yang, Jia Deng:
Stacked Hourglass Networks for Human Pose Estimation. ECCV (8) 2016: 483-499 - [c20]Mingzhe Wang, Mahmoud Azab, Noriyuki Kojima, Rada Mihalcea, Jia Deng:
Structured Matching for Phrase Localization. ECCV (8) 2016: 696-711 - [c19]Weifeng Chen, Zhao Fu, Dawei Yang, Jia Deng:
Single-Image Depth Perception in the Wild. NIPS 2016: 730-738 - [i5]Alejandro Newell, Kaiyu Yang, Jia Deng:
Stacked Hourglass Networks for Human Pose Estimation. CoRR abs/1603.06937 (2016) - [i4]Weifeng Chen, Zhao Fu, Dawei Yang, Jia Deng:
Single-Image Depth Perception in the Wild. CoRR abs/1604.03901 (2016) - [i3]Alejandro Newell, Jia Deng:
Associative Embedding: End-to-End Learning for Joint Detection and Grouping. CoRR abs/1611.05424 (2016) - 2015
- [j2]Vicente Ordonez, Wei Liu, Jia Deng, Yejin Choi, Alexander C. Berg, Tamara L. Berg:
Predicting Entry-Level Categories. Int. J. Comput. Vis. 115(1): 29-43 (2015) - [j1]Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael S. Bernstein, Alexander C. Berg, Li Fei-Fei:
ImageNet Large Scale Visual Recognition Challenge. Int. J. Comput. Vis. 115(3): 211-252 (2015) - [c18]Vignesh Ramanathan, Congcong Li, Jia Deng, Wei Han, Zhen Li, Kunlong Gu, Yang Song, Samy Bengio, Chuck Rosenberg, Li Fei-Fei:
Learning semantic relationships for better action retrieval in images. CVPR 2015: 1100-1109 - [c17]Yu-Wei Chao, Zhan Wang, Rada Mihalcea, Jia Deng:
Mining semantic affordances of visual object categories. CVPR 2015: 4259-4267 - [c16]Yu-Wei Chao, Zhan Wang, Yugeng He, Jiaxuan Wang, Jia Deng:
HICO: A Benchmark for Recognizing Human-Object Interactions in Images. ICCV 2015: 1017-1025 - [c15]Nan Ding, Jia Deng, Kevin P. Murphy, Hartmut Neven:
Probabilistic Label Relation Graphs with Ising Models. ICCV 2015: 1161-1169 - [i2]Nan Ding, Jia Deng, Kevin Murphy, Hartmut Neven:
Probabilistic Label Relation Graphs with Ising Models. CoRR abs/1503.01428 (2015) - 2014
- [c14]Jia Deng, Olga Russakovsky, Jonathan Krause, Michael S. Bernstein, Alexander C. Berg, Li Fei-Fei:
Scalable multi-label annotation. CHI 2014: 3099-3102 - [c13]Jia Deng, Nan Ding, Yangqing Jia, Andrea Frome, Kevin Murphy, Samy Bengio, Yuan Li, Hartmut Neven, Hartwig Adam:
Large-Scale Object Classification Using Label Relation Graphs. ECCV (1) 2014: 48-64 - [c12]Jonathan Krause, Timnit Gebru, Jia Deng, Li-Jia Li, Li Fei-Fei:
Learning Features and Parts for Fine-Grained Recognition. ICPR 2014: 26-33 - [i1]Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael S. Bernstein, Alexander C. Berg, Li Fei-Fei:
ImageNet Large Scale Visual Recognition Challenge. CoRR abs/1409.0575 (2014) - 2013
- [c11]Jia Deng, Jonathan Krause, Li Fei-Fei:
Fine-Grained Crowdsourcing for Fine-Grained Recognition. CVPR 2013: 580-587 - [c10]Olga Russakovsky, Jia Deng, Zhiheng Huang, Alexander C. Berg, Li Fei-Fei:
Detecting Avocados to Zucchinis: What Have We Done, and Where Are We Going? ICCV 2013: 2064-2071 - [c9]Vicente Ordonez, Jia Deng, Yejin Choi, Alexander C. Berg, Tamara L. Berg:
From Large Scale Image Categorization to Entry-Level Categories. ICCV 2013: 2768-2775 - [c8]Jonathan Krause, Michael Stark, Jia Deng, Li Fei-Fei:
3D Object Representations for Fine-Grained Categorization. ICCV Workshops 2013: 554-561 - 2012
- [b1]Jia Deng:
Large Scale Visual Recognition. Princeton University, USA, 2012 - [c7]Jia Deng, Jonathan Krause, Alexander C. Berg, Li Fei-Fei:
Hedging your bets: Optimizing accuracy-specificity trade-offs in large scale visual recognition. CVPR 2012: 3450-3457 - [c6]Hao Su, Jia Deng, Li Fei-Fei:
Crowdsourcing Annotations for Visual Object Detection. HCOMP@AAAI 2012 - 2011
- [c5]Jia Deng, Alexander C. Berg, Li Fei-Fei:
Hierarchical semantic indexing for large scale image retrieval. CVPR 2011: 785-792 - [c4]Jia Deng, Sanjeev Satheesh, Alexander C. Berg, Li Fei-Fei:
Fast and Balanced: Efficient Label Tree Learning for Large Scale Object Recognition. NIPS 2011: 567-575 - 2010
- [c3]Jia Deng, Alexander C. Berg, Kai Li, Li Fei-Fei:
What Does Classifying More Than 10, 000 Image Categories Tell Us? ECCV (5) 2010: 71-84
2000 – 2009
- 2009
- [c2]Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, Li Fei-Fei:
ImageNet: A large-scale hierarchical image database. CVPR 2009: 248-255 - 2008
- [c1]Brendan Collins, Jia Deng, Kai Li, Li Fei-Fei:
Towards Scalable Dataset Construction: An Active Learning Approach. ECCV (1) 2008: 86-98
Coauthor Index
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