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2020 – today
- 2022
[i78]Zhiqiu Lin, Jia Shi, Deepak Pathak, Deva Ramanan:
The CLEAR Benchmark: Continual LEArning on Real-World Imagery. CoRR abs/2201.06289 (2022)- [i77]Shaden Alshammari, Yu-Xiong Wang, Deva Ramanan, Shu Kong:
Long-Tailed Recognition via Weight Balancing. CoRR abs/2203.14197 (2022) - [i76]Neehar Peri, Jonathon Luiten, Mengtian Li, Aljosa Osep, Laura Leal-Taixé, Deva Ramanan:
Forecasting from LiDAR via Future Object Detection. CoRR abs/2203.16297 (2022) - [i75]Joshua Spisak, Andrew Saba, Nayana Suvarna, Brian Mao, Chuan Tian Zhang, Chris Chang, Sebastian Scherer, Deva Ramanan:
Robust Modeling and Controls for Racing on the Edge. CoRR abs/2205.10841 (2022) - [i74]Ali Athar, Jonathon Luiten, Alexander Hermans, Deva Ramanan, Bastian Leibe:
Differentiable Soft-Masked Attention. CoRR abs/2206.00182 (2022) - 2021
- [c119]Gengshan Yang, Deva Ramanan:
Learning To Segment Rigid Motions From Two Frames. CVPR 2021: 1266-1275 - [c118]Ravi Teja Mullapudi, Fait Poms, William R. Mark, Deva Ramanan, Kayvon Fatahalian:
Background Splitting: Finding Rare Classes in a Sea of Background. CVPR 2021: 8043-8052 - [c117]Peiyun Hu, Aaron Huang, John M. Dolan, David Held, Deva Ramanan:
Safe Local Motion Planning With Self-Supervised Freespace Forecasting. CVPR 2021: 12732-12741 - [c116]Gengshan Yang, Deqing Sun, Varun Jampani, Daniel Vlasic, Forrester Cole, Huiwen Chang, Deva Ramanan, William T. Freeman, Ce Liu:
LASR: Learning Articulated Shape Reconstruction From a Monocular Video. CVPR 2021: 15980-15989 - [c115]Shu Kong, Deva Ramanan:
OpenGAN: Open-Set Recognition via Open Data Generation. ICCV 2021: 793-802 - [c114]Tarasha Khurana, Achal Dave, Deva Ramanan:
Detecting Invisible People. ICCV 2021: 3154-3164 - [c113]Ravi Teja Mullapudi, Fait Poms, William R. Mark, Deva Ramanan, Kayvon Fatahalian:
Learning Rare Category Classifiers on a Tight Labeling Budget. ICCV 2021: 8403-8412 - [c112]Vaishaal Shankar, Achal Dave, Rebecca Roelofs, Deva Ramanan, Benjamin Recht, Ludwig Schmidt:
Do Image Classifiers Generalize Across Time? ICCV 2021: 9641-9649 - [c111]Fait Poms, Vishnu Sarukkai, Ravi Teja Mullapudi, Nimit Sharad Sohoni, William R. Mark, Deva Ramanan, Kayvon Fatahalian:
Low-Shot Validation: Active Importance Sampling for Estimating Classifier Performance on Rare Categories. ICCV 2021: 10685-10694 - [c110]Chittesh Thavamani, Mengtian Li, Nicolas Cebron, Deva Ramanan:
FOVEA: Foveated Image Magnification for Autonomous Navigation. ICCV 2021: 15519-15528 - [c109]Kangle Deng, Aayush Bansal, Deva Ramanan:
Unsupervised Audiovisual Synthesis via Exemplar Autoencoders. ICLR 2021 - [c108]Zhiqiu Lin, Jia Shi, Deepak Pathak, Deva Ramanan:
The CLEAR Benchmark: Continual LEArning on Real-World Imagery. NeurIPS Datasets and Benchmarks 2021 - [c107]Benjamin Wilson, William Qi, Tanmay Agarwal, John Lambert, Jagjeet Singh, Siddhesh Khandelwal, Bowen Pan, Ratnesh Kumar, Andrew Hartnett, Jhony Kaesemodel Pontes, Deva Ramanan, Peter Carr, James Hays:
Argoverse 2: Next Generation Datasets for Self-Driving Perception and Forecasting. NeurIPS Datasets and Benchmarks 2021 - [c106]Gengshan Yang, Deqing Sun, Varun Jampani, Daniel Vlasic, Forrester Cole, Ce Liu, Deva Ramanan:
ViSER: Video-Specific Surface Embeddings for Articulated 3D Shape Reconstruction. NeurIPS 2021: 19326-19338 - [c105]Jason Zhang, Gengshan Yang, Shubham Tulsiani, Deva Ramanan:
NeRS: Neural Reflectance Surfaces for Sparse-view 3D Reconstruction in the Wild. NeurIPS 2021: 29835-29847 - [i73]Gengshan Yang, Deva Ramanan:
Learning to Segment Rigid Motions from Two Frames. CoRR abs/2101.03694 (2021) - [i72]Achal Dave, Piotr Dollár, Deva Ramanan, Alexander Kirillov, Ross B. Girshick:
Evaluating Large-Vocabulary Object Detectors: The Devil is in the Details. CoRR abs/2102.01066 (2021) - [i71]Kevin Wang, Deva Ramanan, Aayush Bansal:
Video Exploration via Video-Specific Autoencoders. CoRR abs/2103.17261 (2021) - [i70]Yi-Ting Chen, Jinghao Shi, Christoph Mertz, Shu Kong, Deva Ramanan:
Multimodal Object Detection via Bayesian Fusion. CoRR abs/2104.02904 (2021) - [i69]Shu Kong, Deva Ramanan:
OpenGAN: Open-Set Recognition via Open Data Generation. CoRR abs/2104.02939 (2021) - [i68]Zhiqiu Lin, Deva Ramanan, Aayush Bansal:
Streaming Self-Training via Domain-Agnostic Unlabeled Images. CoRR abs/2104.03309 (2021) - [i67]Yang Liu, Idil Esen Zulfikar, Jonathon Luiten, Achal Dave, Aljosa Osep, Deva Ramanan, Bastian Leibe, Laura Leal-Taixé:
Opening up Open-World Tracking. CoRR abs/2104.11221 (2021) - [i66]Gengshan Yang, Deqing Sun, Varun Jampani, Daniel Vlasic, Forrester Cole, Huiwen Chang, Deva Ramanan, William T. Freeman, Ce Liu:
LASR: Learning Articulated Shape Reconstruction from a Monocular Video. CoRR abs/2105.02976 (2021) - [i65]Kangle Deng, Andrew Liu, Jun-Yan Zhu, Deva Ramanan:
Depth-supervised NeRF: Fewer Views and Faster Training for Free. CoRR abs/2107.02791 (2021) - [i64]Chittesh Thavamani, Mengtian Li, Nicolas Cebron, Deva Ramanan:
FOVEA: Foveated Image Magnification for Autonomous Navigation. CoRR abs/2108.12102 (2021) - [i63]Fait Poms, Vishnu Sarukkai, Ravi Teja Mullapudi, Nimit Sharad Sohoni, William R. Mark, Deva Ramanan, Kayvon Fatahalian:
Low-Shot Validation: Active Importance Sampling for Estimating Classifier Performance on Rare Categories. CoRR abs/2109.05720 (2021) - [i62]Jason Y. Zhang, Gengshan Yang, Shubham Tulsiani, Deva Ramanan:
NeRS: Neural Reflectance Surfaces for Sparse-view 3D Reconstruction in the Wild. CoRR abs/2110.07604 (2021) - [i61]Ali Athar, Jonathon Luiten, Alexander Hermans, Deva Ramanan, Bastian Leibe:
HODOR: High-level Object Descriptors for Object Re-segmentation in Video Learned from Static Images. CoRR abs/2112.09131 (2021) - [i60]Haithem Turki, Deva Ramanan, Mahadev Satyanarayanan:
Mega-NeRF: Scalable Construction of Large-Scale NeRFs for Virtual Fly-Throughs. CoRR abs/2112.10703 (2021) - [i59]Gengshan Yang, Minh Vo, Natalia Neverova, Deva Ramanan, Andrea Vedaldi, Hanbyul Joo:
BANMo: Building Animatable 3D Neural Models from Many Casual Videos. CoRR abs/2112.12761 (2021) - 2020
- [j19]Peiyun Hu
, David Held, Deva Ramanan:
Learning to Optimally Segment Point Clouds. IEEE Robotics Autom. Lett. 5(2): 875-882 (2020) - [c104]Gengshan Yang, Deva Ramanan:
Upgrading Optical Flow to 3D Scene Flow Through Optical Expansion. CVPR 2020: 1331-1340 - [c103]Aayush Bansal, Minh Vo, Yaser Sheikh, Deva Ramanan, Srinivasa G. Narasimhan:
4D Visualization of Dynamic Events From Unconstrained Multi-View Videos. CVPR 2020: 5365-5374 - [c102]Peiyun Hu, Jason Ziglar, David Held, Deva Ramanan:
What You See is What You Get: Exploiting Visibility for 3D Object Detection. CVPR 2020: 10998-11006 - [c101]Jason Y. Zhang, Sam Pepose, Hanbyul Joo, Deva Ramanan, Jitendra Malik, Angjoo Kanazawa:
Perceiving 3D Human-Object Spatial Arrangements from a Single Image in the Wild. ECCV (12) 2020: 34-51 - [c100]Achal Dave, Tarasha Khurana, Pavel Tokmakov, Cordelia Schmid, Deva Ramanan:
TAO: A Large-Scale Benchmark for Tracking Any Object. ECCV (5) 2020: 436-454 - [c99]Mengtian Li, Yu-Xiong Wang, Deva Ramanan:
Towards Streaming Perception. ECCV (2) 2020: 473-488 - [c98]Rohit Girdhar, Deva Ramanan:
CATER: A diagnostic dataset for Compositional Actions & TEmporal Reasoning. ICLR 2020 - [c97]Jessica Lee, Deva Ramanan, Rohit Girdhar:
MetaPix: Few-Shot Video Retargeting. ICLR 2020 - [c96]Mengtian Li, Ersin Yumer, Deva Ramanan:
Budgeted Training: Rethinking Deep Neural Network Training Under Resource Constraints. ICLR 2020 - [c95]William Qi, Ravi Teja Mullapudi, Saurabh Gupta, Deva Ramanan:
Learning to Move with Affordance Maps. ICLR 2020 - [i58]William Qi, Ravi Teja Mullapudi, Saurabh Gupta, Deva Ramanan:
Learning to Move with Affordance Maps. CoRR abs/2001.02364 (2020) - [i57]Kangle Deng, Aayush Bansal, Deva Ramanan:
Unsupervised Any-to-Many Audiovisual Synthesis via Exemplar Autoencoders. CoRR abs/2001.04463 (2020) - [i56]Ligong Han, Robert F. Murphy, Deva Ramanan:
Learning Generative Models of Tissue Organization with Supervised GANs. CoRR abs/2004.00140 (2020) - [i55]Achal Dave, Tarasha Khurana, Pavel Tokmakov, Cordelia Schmid, Deva Ramanan:
TAO: A Large-Scale Benchmark for Tracking Any Object. CoRR abs/2005.10356 (2020) - [i54]Mengtian Li, Yu-Xiong Wang, Deva Ramanan:
Towards Streaming Image Understanding. CoRR abs/2005.10420 (2020) - [i53]Aayush Bansal, Minh Vo, Yaser Sheikh, Deva Ramanan, Srinivasa G. Narasimhan:
4D Visualization of Dynamic Events from Unconstrained Multi-View Videos. CoRR abs/2005.13532 (2020) - [i52]Jason Y. Zhang, Sam Pepose, Hanbyul Joo, Deva Ramanan, Jitendra Malik, Angjoo Kanazawa:
Perceiving 3D Human-Object Spatial Arrangements from a Single Image in the Wild. CoRR abs/2007.15649 (2020) - [i51]Siddhesh Khandelwal, William Qi, Jagjeet Singh, Andrew Hartnett, Deva Ramanan:
What-If Motion Prediction for Autonomous Driving. CoRR abs/2008.10587 (2020) - [i50]Ravi Teja Mullapudi, Fait Poms, William R. Mark, Deva Ramanan, Kayvon Fatahalian:
Background Splitting: Finding Rare Classes in a Sea of Background. CoRR abs/2008.12873 (2020) - [i49]Tarasha Khurana, Achal Dave, Deva Ramanan:
Detecting Invisible People. CoRR abs/2012.08419 (2020)
2010 – 2019
- 2019
- [j18]Bailey Kong, James Steven Supancic III, Deva Ramanan, Charless C. Fowlkes:
Cross-Domain Image Matching with Deep Feature Maps. Int. J. Comput. Vis. 127(11-12): 1738-1750 (2019) - [c94]Aayush Bansal, Yaser Sheikh, Deva Ramanan:
Shapes and Context: In-The-Wild Image Synthesis & Manipulation. CVPR 2019: 2317-2326 - [c93]Gengshan Yang, Joshua Manela, Michael Happold, Deva Ramanan:
Hierarchical Deep Stereo Matching on High-Resolution Images. CVPR 2019: 5515-5524 - [c92]Ming-Fang Chang, John Lambert, Patsorn Sangkloy, Jagjeet Singh, Slawomir Bak, Andrew Hartnett, De Wang, Peter Carr, Simon Lucey, Deva Ramanan, James Hays:
Argoverse: 3D Tracking and Forecasting With Rich Maps. CVPR 2019: 8748-8757 - [c91]Ishan Nigam, Pavel Tokmakov, Deva Ramanan:
Towards Latent Attribute Discovery From Triplet Similarities. ICCV 2019: 402-410 - [c90]Rohit Girdhar, Du Tran, Lorenzo Torresani, Deva Ramanan:
DistInit: Learning Video Representations Without a Single Labeled Video. ICCV 2019: 852-861 - [c89]Ravi Teja Mullapudi, Steven Chen, Keyi Zhang, Deva Ramanan, Kayvon Fatahalian:
Online Model Distillation for Efficient Video Inference. ICCV 2019: 3572-3581 - [c88]Phuc Xuan Nguyen, Deva Ramanan, Charless C. Fowlkes:
Weakly-Supervised Action Localization With Background Modeling. ICCV 2019: 5501-5510 - [c87]Yu-Xiong Wang, Deva Ramanan, Martial Hebert:
Meta-Learning to Detect Rare Objects. ICCV 2019: 9924-9933 - [c86]Siva Chaitanya Mynepalli, Peiyun Hu, Deva Ramanan:
Recognizing Tiny Faces. ICCV Workshops 2019: 1121-1130 - [c85]Achal Dave, Pavel Tokmakov, Deva Ramanan:
Towards Segmenting Anything That Moves. ICCV Workshops 2019: 1493-1502 - [c84]Bhavan Jasani, Rohit Girdhar, Deva Ramanan:
Are we Asking the Right Questions in MovieQA? ICCV Workshops 2019: 1879-1882 - [c83]Peiyun Hu, Zachary C. Lipton, Anima Anandkumar, Deva Ramanan:
Active Learning with Partial Feedback. ICLR (Poster) 2019 - [c82]Gengshan Yang, Peiyun Hu, Deva Ramanan:
Inferring Distributions Over Depth from a Single Image. IROS 2019: 6090-6096 - [c81]Gengshan Yang, Deva Ramanan:
Volumetric Correspondence Networks for Optical Flow. NeurIPS 2019: 793-803 - [c80]Mengtian Li, Zhe L. Lin, Radomír Mech, Ersin Yumer, Deva Ramanan:
Photo-Sketching: Inferring Contour Drawings From Images. WACV 2019: 1403-1412 - [i48]Mengtian Li, Zhe Lin, Radomír Mech, Ersin Yumer, Deva Ramanan:
Photo-Sketching: Inferring Contour Drawings from Images. CoRR abs/1901.00542 (2019) - [i47]Rohit Girdhar, Du Tran, Lorenzo Torresani, Deva Ramanan:
DistInit: Learning Video Representations without a Single Labeled Video. CoRR abs/1901.09244 (2019) - [i46]Achal Dave, Pavel Tokmakov, Deva Ramanan:
Towards Segmenting Everything That Moves. CoRR abs/1902.03715 (2019) - [i45]Mengtian Li, Ersin Yumer, Deva Ramanan:
Budgeted Training: Rethinking Deep Neural Network Training Under Resource Constraints. CoRR abs/1905.04753 (2019) - [i44]Vaishaal Shankar, Achal Dave, Rebecca Roelofs, Deva Ramanan, Benjamin Recht, Ludwig Schmidt:
A systematic framework for natural perturbations from videos. CoRR abs/1906.02168 (2019) - [i43]Aayush Bansal, Yaser Sheikh, Deva Ramanan:
Shapes and Context: In-the-Wild Image Synthesis & Manipulation. CoRR abs/1906.04728 (2019) - [i42]Yu-Xiong Wang, Deva Ramanan, Martial Hebert:
Growing a Brain: Fine-Tuning by Increasing Model Capacity. CoRR abs/1907.07844 (2019) - [i41]Phuc Xuan Nguyen, Deva Ramanan, Charless C. Fowlkes:
Weakly-supervised Action Localization with Background Modeling. CoRR abs/1908.06552 (2019) - [i40]Jessica Lee, Deva Ramanan, Rohit Girdhar:
MetaPix: Few-Shot Video Retargeting. CoRR abs/1910.04742 (2019) - [i39]Rohit Girdhar, Deva Ramanan:
CATER: A diagnostic dataset for Compositional Actions and TEmporal Reasoning. CoRR abs/1910.04744 (2019) - [i38]Achal Dave, Pavel Tokmakov, Cordelia Schmid, Deva Ramanan:
Learning to Track Any Object. CoRR abs/1910.11844 (2019) - [i37]Ming-Fang Chang, John Lambert, Patsorn Sangkloy, Jagjeet Singh, Slawomir Bak, Andrew Hartnett, De Wang, Peter Carr, Simon Lucey, Deva Ramanan, James Hays:
Argoverse: 3D Tracking and Forecasting with Rich Maps. CoRR abs/1911.02620 (2019) - [i36]Bhavan Jasani, Rohit Girdhar, Deva Ramanan:
Are we asking the right questions in MovieQA? CoRR abs/1911.03083 (2019) - [i35]Peiyun Hu, David Held, Deva Ramanan:
Learning to Optimally Segment Point Clouds. CoRR abs/1912.04976 (2019) - [i34]Peiyun Hu, Jason Ziglar, David Held, Deva Ramanan:
What You See is What You Get: Exploiting Visibility for 3D Object Detection. CoRR abs/1912.04986 (2019) - [i33]Gengshan Yang, Peiyun Hu, Deva Ramanan:
Inferring Distributions Over Depth from a Single Image. CoRR abs/1912.06268 (2019) - [i32]Gengshan Yang, Joshua Manela, Michael Happold, Deva Ramanan:
Hierarchical Deep Stereo Matching on High-resolution Images. CoRR abs/1912.06704 (2019) - 2018
- [j17]James Steven Supancic III, Grégory Rogez, Yi Yang, Jamie Shotton, Deva Ramanan:
Depth-Based Hand Pose Estimation: Methods, Data, and Challenges. Int. J. Comput. Vis. 126(11): 1180-1198 (2018) - [j16]Zachary Pezzementi, Trenton Tabor, Peiyun Hu, Jonathan K. Chang, Deva Ramanan, Carl Wellington, Benzun P. Wisely Babu, Herman Herman:
Comparing apples and oranges: Off-road pedestrian detection on the National Robotics Engineering Center agricultural person-detection dataset. J. Field Robotics 35(4): 545-563 (2018) - [c79]Mengtian Li, László A. Jeni, Deva Ramanan:
Brute-Force Facial Landmark Analysis With a 140, 000-Way Classifier. AAAI 2018: 7032-7040 - [c78]Aayush Bansal, Shugao Ma, Deva Ramanan, Yaser Sheikh:
Recycle-GAN: Unsupervised Video Retargeting. ECCV (5) 2018: 122-138 - [c77]Liang-Yan Gui, Yu-Xiong Wang, Deva Ramanan, José M. F. Moura:
Few-Shot Human Motion Prediction via Meta-learning. ECCV (8) 2018: 441-459 - [c76]Aayush Bansal, Yaser Sheikh, Deva Ramanan:
PixelNN: Example-based Image Synthesis. ICLR (Poster) 2018 - [c75]Phuc Xuan Nguyen, Deva Ramanan, Charless C. Fowlkes:
Active Testing: An Efficient and Robust Framework for Estimating Accuracy. ICML 2018: 3756-3765 - [c74]Ligong Han, Robert F. Murphy, Deva Ramanan:
Learning Generative Models of Tissue Organization with Supervised GANs. WACV 2018: 682-690 - [c73]Ishan Nigam, Chen Huang, Deva Ramanan:
Ensemble Knowledge Transfer for Semantic Segmentation. WACV 2018: 1499-1508 - [c72]Jingyan Wang, Olga Russakovsky, Deva Ramanan:
The More You Look, the More You See: Towards General Object Understanding Through Recursive Refinement. WACV 2018: 1794-1803 - [i31]Mengtian Li, László A. Jeni, Deva Ramanan:
Brute-Force Facial Landmark Analysis With A 140, 000-Way Classifier. CoRR abs/1802.01777 (2018) - [i30]Peiyun Hu, Zachary C. Lipton, Anima Anandkumar, Deva Ramanan:
Active Learning with Partial Feedback. CoRR abs/1802.07427 (2018) - [i29]Bailey Kong, James Steven Supancic III, Deva Ramanan, Charless C. Fowlkes:
Cross-Domain Image Matching with Deep Feature Maps. CoRR abs/1804.02367 (2018) - [i28]Phuc Xuan Nguyen, Deva Ramanan, Charless C. Fowlkes:
Active Testing: An Efficient and Robust Framework for Estimating Accuracy. CoRR abs/1807.00493 (2018) - [i27]Aayush Bansal, Shugao Ma, Deva Ramanan, Yaser Sheikh:
Recycle-GAN: Unsupervised Video Retargeting. CoRR abs/1808.05174 (2018) - [i26]Ravi Teja Mullapudi, Steven Chen, Keyi Zhang, Deva Ramanan, Kayvon Fatahalian:
Online Model Distillation for Efficient Video Inference. CoRR abs/1812.02699 (2018) - 2017
- [c71]Bailey Kong, James Steven Supancic III, Deva Ramanan, Charless C. Fowlkes:
Fine-Grained Forensic Matching. BMVC 2017 - [c70]Peiyun Hu, Deva Ramanan:
Finding Tiny Faces. CVPR 2017: 1522-1530 - [c69]Achal Dave, Olga Russakovsky, Deva Ramanan:
Predictive-Corrective Networks for Action Detection. CVPR 2017: 2067-2076 - [c68]Yu-Xiong Wang, Deva Ramanan, Martial Hebert:
Growing a Brain: Fine-Tuning by Increasing Model Capacity. CVPR 2017: 3029-3038 - [c67]Rohit Girdhar, Deva Ramanan, Abhinav Gupta, Josef Sivic, Bryan C. Russell:
ActionVLAD: Learning Spatio-Temporal Aggregation for Action Classification. CVPR 2017: 3165-3174 - [c66]Shiyu Huang, Deva Ramanan:
Expecting the Unexpected: Training Detectors for Unusual Pedestrians with Adversarial Imposters. CVPR 2017: 4664-4673 - [c65]Ching-Hang Chen, Deva Ramanan:
3D Human Pose Estimation = 2D Pose Estimation + Matching. CVPR 2017: 5759-5767 - [c64]Manuel Günther, Peiyun Hu, Christian Herrmann, Chi-Ho Chan, Min Jiang, Shufan Yang, Akshay Raj Dhamija, Deva Ramanan, Jürgen Beyerer, Josef Kittler, Mohamad Al Jazaery, Mohammad Iqbal Nouyed, Guodong Guo, Cezary Stankiewicz, Terrance E. Boult:
Unconstrained Face Detection and Open-Set Face Recognition Challenge. IJCB 2017: 697-706 - [c63]Chen Huang, Simon Lucey, Deva Ramanan:
Learning Policies for Adaptive Tracking with Deep Feature Cascades. ICCV 2017: 105-114 - [c62]James Steven Supancic III, Deva Ramanan:
Tracking as Online Decision-Making: Learning a Policy from Streaming Videos with Reinforcement Learning. ICCV 2017: 322-331 - [c61]Hamed Kiani Galoogahi, Ashton Fagg, Chen Huang, Deva Ramanan, Simon Lucey:
Need for Speed: A Benchmark for Higher Frame Rate Object Tracking. ICCV 2017: 1134-1143 - [c60]Rohit Girdhar, Deva Ramanan:
Attentional Pooling for Action Recognition. NIPS 2017: 34-45 - [c59]Yu-Xiong Wang, Deva Ramanan, Martial Hebert:
Learning to Model the Tail. NIPS 2017: 7029-7039 - [i25]Aayush Bansal, Xinlei Chen, Bryan C. Russell, Abhinav Gupta, Deva Ramanan:
PixelNet: Representation of the pixels, by the pixels, and for the pixels. CoRR abs/1702.06506 (2017) - [i24]Hamed Kiani Galoogahi, Ashton Fagg, Chen Huang, Deva Ramanan, Simon Lucey:
Need for Speed: A Benchmark for Higher Frame Rate Object Tracking. CoRR abs/1703.05884 (2017) - [i23]Shiyu Huang, Deva Ramanan:
Recognition in-the-Tail: Training Detectors for Unusual Pedestrians with Synthetic Imposters. CoRR abs/1703.06283 (2017) - [i22]Rohit Girdhar, Deva Ramanan, Abhinav Gupta, Josef Sivic, Bryan C. Russell:
ActionVLAD: Learning spatio-temporal aggregation for action classification. CoRR abs/1704.02895 (2017) - [i21]Achal Dave, Olga Russakovsky, Deva Ramanan:
Predictive-Corrective Networks for Action Detection. CoRR abs/1704.03615 (2017) - [i20]James Steven Supancic III, Deva Ramanan:
Tracking as Online Decision-Making: Learning a Policy from Streaming Videos with Reinforcement Learning. CoRR abs/1707.04991 (2017) - [i19]