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2020 – today
- 2024
[c169]Amy Lin, Jason Y. Zhang, Deva Ramanan, Shubham Tulsiani:
RelPose++: Recovering 6D Poses from Sparse-view Observations. 3DV 2024: 106-115- [c168]Jonathon Luiten, Georgios Kopanas, Bastian Leibe, Deva Ramanan:
Dynamic 3D Gaussians: Tracking by Persistent Dynamic View Synthesis. 3DV 2024: 800-809 - [c167]Baiqi Li, Zhiqiu Lin, Deepak Pathak, Jiayao Li, Yixin Fei, Kewen Wu, Xide Xia, Pengchuan Zhang, Graham Neubig, Deva Ramanan:
Evaluating and Improving Compositional Text-to-Visual Generation. CVPR Workshops 2024: 5290-5301 - [c166]Shihong Liu, Samuel Yu, Zhiqiu Lin, Deepak Pathak, Deva Ramanan:
Language Models as Black-Box Optimizers for Vision-Language Models. CVPR 2024: 12687-12697 - [c165]Shubham Parashar, Zhiqiu Lin, Tian Liu, Xiangjue Dong, Yanan Li, Deva Ramanan, James Caverlee, Shu Kong:
The Neglected Tails in Vision-Language Models. CVPR 2024: 12988-12997 - [c164]Haithem Turki, Vasu Agrawal, Samuel Rota Bulò, Lorenzo Porzi, Peter Kontschieder, Deva Ramanan, Michael Zollhöfer, Christian Richardt:
HybridNeRF: Efficient Neural Rendering via Adaptive Volumetric Surfaces. CVPR 2024: 19647-19656 - [c163]Nikhil Varma Keetha, Jay Karhade, Krishna Murthy Jatavallabhula, Gengshan Yang, Sebastian Scherer, Deva Ramanan, Jonathon Luiten:
SplaTAM: Splat, Track & Map 3D Gaussians for Dense RGB-D SLAM. CVPR 2024: 21357-21366 - [c162]Aljosa Osep, Tim Meinhardt, Francesco Ferroni, Neehar Peri, Deva Ramanan, Laura Leal-Taixé:
Better Call SAL: Towards Learning to Segment Anything in Lidar. ECCV (39) 2024: 71-90 - [c161]Ishan Khatri, Kyle Vedder, Neehar Peri, Deva Ramanan, James Hays:
I Can't Believe It's Not Scene Flow! ECCV (18) 2024: 242-257 - [c160]Zhiqiu Lin, Deepak Pathak, Baiqi Li, Jiayao Li, Xide Xia, Graham Neubig, Pengchuan Zhang, Deva Ramanan:
Evaluating Text-to-Visual Generation with Image-to-Text Generation. ECCV (9) 2024: 366-384 - [c159]Jason Y. Zhang, Amy Lin, Moneish Kumar, Tzu-Hsuan Yang, Deva Ramanan, Shubham Tulsiani:
Cameras as Rays: Pose Estimation via Ray Diffusion. ICLR 2024 - [c158]Kyle Vedder, Neehar Peri, Nathaniel Chodosh, Ishan Khatri, Eric Eaton, Dinesh Jayaraman, Yang Liu, Deva Ramanan, James Hays:
ZeroFlow: Scalable Scene Flow via Distillation. ICLR 2024 - [c157]Zhiqiu Lin, Xinyue Chen, Deepak Pathak, Pengchuan Zhang, Deva Ramanan:
Revisiting the Role of Language Priors in Vision-Language Models. ICML 2024 - [c156]Nathaniel Chodosh, Deva Ramanan, Simon Lucey
:
Re-Evaluating LiDAR Scene Flow. WACV 2024: 5993-6003 - [i133]Shubham Parashar, Zhiqiu Lin, Tian Liu, Xiangjue Dong, Yanan Li, Deva Ramanan, James Caverlee, Shu Kong:
The Neglected Tails of Vision-Language Models. CoRR abs/2401.12425 (2024) - [i132]Kangle Deng, Timothy Omernick, Alexander Weiss, Deva Ramanan, Jun-Yan Zhu, Tinghui Zhou, Maneesh Agrawala:
FlashTex: Fast Relightable Mesh Texturing with LightControlNet. CoRR abs/2402.13251 (2024) - [i131]Jason Y. Zhang, Amy Lin, Moneish Kumar, Tzu-Hsuan Yang, Deva Ramanan, Shubham Tulsiani:
Cameras as Rays: Pose Estimation via Ray Diffusion. CoRR abs/2402.14817 (2024) - [i130]Ishan Khatri, Kyle Vedder, Neehar Peri, Deva Ramanan, James Hays:
I Can't Believe It's Not Scene Flow! CoRR abs/2403.04739 (2024) - [i129]Aljosa Osep, Tim Meinhardt, Francesco Ferroni, Neehar Peri, Deva Ramanan, Laura Leal-Taixé:
Better Call SAL: Towards Learning to Segment Anything in Lidar. CoRR abs/2403.13129 (2024) - [i128]Zhiqiu Lin, Deepak Pathak, Baiqi Li, Jiayao Li, Xide Xia, Graham Neubig, Pengchuan Zhang, Deva Ramanan:
Evaluating Text-to-Visual Generation with Image-to-Text Generation. CoRR abs/2404.01291 (2024) - [i127]Tarasha Khurana, Deva Ramanan:
Predicting Long-horizon Futures by Conditioning on Geometry and Time. CoRR abs/2404.11554 (2024) - [i126]Jacob Yeung, Andrew F. Luo, Gabriel Sarch, Margaret M. Henderson, Deva Ramanan, Michael J. Tarr:
Neural Representations of Dynamic Visual Stimuli. CoRR abs/2406.02659 (2024) - [i125]Mehar Khurana, Neehar Peri, Deva Ramanan, James Hays:
Shelf-Supervised Multi-Modal Pre-Training for 3D Object Detection. CoRR abs/2406.10115 (2024) - [i124]Arun Balajee Vasudevan, Neehar Peri, Jeff Schneider, Deva Ramanan:
Planning with Adaptive World Models for Autonomous Driving. CoRR abs/2406.10714 (2024) - [i123]Baiqi Li, Zhiqiu Lin, Deepak Pathak, Jiayao Li, Yixin Fei, Kewen Wu, Tiffany Ling, Xide Xia, Pengchuan Zhang, Graham Neubig, Deva Ramanan:
GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation. CoRR abs/2406.13743 (2024) - [i122]Nathaniel Chodosh, Anish Madan, Deva Ramanan, Simon Lucey:
Simultaneous Map and Object Reconstruction. CoRR abs/2406.13896 (2024) - [i121]Andrew Saba, Aderotimi Adetunji, Adam Johnson, Aadi Kothari, Matthew Sivaprakasam, Joshua Spisak, Prem Bharatia, Arjun Chauhan, Brendan Duff Jr., Noah Gasparro, Charles King, Ryan Larkin, Brian Mao, Micah Nye, Anjali Parashar, Joseph Attias, Aurimas Balciunas, Austin Brown, Chris Chang, Ming Gao, Cindy Heredia, Andrew Keats, Jose Lavariega, William Muckelroy III, Andre Slavescu, Nickolas Stathas, Nayana Suvarna, Chuan Tian Zhang, Sebastian Scherer, Deva Ramanan:
Fast and Modular Autonomy Software for Autonomous Racing Vehicles. CoRR abs/2408.15425 (2024) - [i120]Jenny Seidenschwarz, Qunjie Zhou, Bardienus Pieter Duisterhof, Deva Ramanan, Laura Leal-Taixé:
DynOMo: Online Point Tracking by Dynamic Online Monocular Gaussian Reconstruction. CoRR abs/2409.02104 (2024) - [i119]Anirudh S. Chakravarthy, Meghana Reddy Ganesina, Peiyun Hu, Laura Leal-Taixé, Shu Kong, Deva Ramanan, Aljosa Osep:
Lidar Panoptic Segmentation in an Open World. CoRR abs/2409.14273 (2024) - [i118]Jeff Tan, Donglai Xiang, Shubham Tulsiani, Deva Ramanan, Gengshan Yang:
DressRecon: Freeform 4D Human Reconstruction from Monocular Video. CoRR abs/2409.20563 (2024) - 2023
- [j20]John Z. Zhang, Shuo Yang, Gengshan Yang, Arun L. Bishop, Swaminathan Gurumurthy, Deva Ramanan, Zachary Manchester:
SLoMo: A General System for Legged Robot Motion Imitation From Casual Videos. IEEE Robotics Autom. Lett. 8(11): 7154-7161 (2023) - [c155]Tarasha Khurana, Peiyun Hu, David Held, Deva Ramanan:
Point Cloud Forecasting as a Proxy for 4D Occupancy Forecasting. CVPR 2023: 1116-1124 - [c154]Aboli Marathe, Deva Ramanan, Rahee Walambe, Ketan Kotecha:
WEDGE: A multi-weather autonomous driving dataset built from generative vision-language models. CVPR Workshops 2023: 3318-3327 - [c153]Kangle Deng, Gengshan Yang, Deva Ramanan, Jun-Yan Zhu:
3D-aware Conditional Image Synthesis. CVPR 2023: 4434-4445 - [c152]Jeff Tan, Gengshan Yang, Deva Ramanan:
Distilling Neural Fields for Real-Time Articulated Shape Reconstruction. CVPR 2023: 4692-4701 - [c151]Chittesh Thavamani, Mengtian Li, Francesco Ferroni, Deva Ramanan:
Learning to Zoom and Unzoom. CVPR 2023: 5086-5095 - [c150]Haithem Turki, Jason Y. Zhang, Francesco Ferroni, Deva Ramanan:
SUDS: Scalable Urban Dynamic Scenes. CVPR 2023: 12375-12385 - [c149]Yang Liu, Shen Yan, Laura Leal-Taixé, James Hays, Deva Ramanan:
Soft Augmentation for Image Classification. CVPR 2023: 16241-16250 - [c148]Gengshan Yang, Chaoyang Wang, N. Dinesh Reddy, Deva Ramanan:
Reconstructing Animatable Categories from Videos. CVPR 2023: 16995-17005 - [c147]Xindi Wu, KwunFung Lau, Francesco Ferroni, Aljosa Osep, Deva Ramanan:
Pix2Map: Cross-Modal Retrieval for Inferring Street Maps from Images. CVPR 2023: 17514-17523 - [c146]Ali Athar, Alexander Hermans, Jonathon Luiten, Deva Ramanan, Bastian Leibe:
TarViS: A Unified Approach for Target-Based Video Segmentation. CVPR 2023: 18738-18748 - [c145]Zhiqiu Lin, Samuel Yu, Zhiyi Kuang, Deepak Pathak, Deva Ramanan:
Multimodality Helps Unimodality: Cross-Modal Few-Shot Learning with Multimodal Models. CVPR 2023: 19325-19337 - [c144]Gengshan Yang, Shuo Yang, John Z. Zhang, Zachary Manchester, Deva Ramanan:
PPR: Physically Plausible Reconstruction from Monocular Videos. ICCV 2023: 3891-3901 - [c143]Chonghyuk Song, Gengshan Yang, Kangle Deng, Jun-Yan Zhu, Deva Ramanan:
Total-Recon: Deformable Scene Reconstruction for Embodied View Synthesis. ICCV 2023: 17625-17636 - [c142]Erica Weng, Hana Hoshino, Deva Ramanan, Kris Kitani:
Joint Metrics Matter: A Better Standard for Trajectory Forecasting. ICCV 2023: 20258-20269 - [c141]Neehar Peri, Mengtian Li, Benjamin Wilson, Yu-Xiong Wang, James Hays, Deva Ramanan:
An Empirical Analysis of Range for 3D Object Detection. ICCV (Workshops) 2023: 4076-4085 - [c140]Shengcao Cao, Mengtian Li, James Hays, Deva Ramanan, Yu-Xiong Wang, Liangyan Gui:
Learning Lightweight Object Detectors via Multi-Teacher Progressive Distillation. ICML 2023: 3577-3598 - [c139]Ziqi Pang, Deva Ramanan, Mengtian Li, Yu-Xiong Wang:
Streaming Motion Forecasting for Autonomous Driving. IROS 2023: 7407-7414 - [c138]Abhinav Agarwalla, Xuhua Huang, Jason Ziglar, Francesco Ferroni, Laura Leal-Taixé, James Hays, Aljosa Osep, Deva Ramanan:
Lidar Panoptic Segmentation and Tracking without Bells and Whistles. IROS 2023: 7667-7674 - [c137]Shilpa Anna George, Haithem Turki, Ziqiang Feng, Deva Ramanan, Padmanabhan Pillai, Mahadev Satyanarayanan:
Low-Bandwidth Self-Improving Transmission of Rare Training Data. MobiCom 2023: 86:1-86:15 - [c136]Shilpa Anna George, Haithem Turki, Ziqiang Feng, Deva Ramanan, Padmanabhan Pillai, Mahadev Satyanarayanan:
Edge-based Privacy-Sensitive Live Learning for Discovery of Training Data. NetAISys@MobiSys 2023: 4:1-4:6 - [c135]Haithem Turki, Michael Zollhöfer, Christian Richardt, Deva Ramanan:
PyNeRF: Pyramidal Neural Radiance Fields. NeurIPS 2023 - [c134]Shubham Gupta, Jeet Kanjani, Mengtian Li, Francesco Ferroni, James Hays, Deva Ramanan, Shu Kong:
Far3Det: Towards Far-Field 3D Detection. WACV 2023: 692-701 - [c133]Ali Athar, Jonathon Luiten, Paul Voigtlaender, Tarasha Khurana, Achal Dave, Bastian Leibe, Deva Ramanan:
BURST: A Benchmark for Unifying Object Recognition, Segmentation and Tracking in Video. WACV 2023: 1674-1683 - [i117]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. CoRR abs/2301.00493 (2023) - [i116]Ali Athar, Alexander Hermans, Jonathon Luiten, Deva Ramanan, Bastian Leibe:
TarViS: A Unified Approach for Target-based Video Segmentation. CoRR abs/2301.02657 (2023) - [i115]Xindi Wu, KwunFung Lau, Francesco Ferroni, Aljosa Osep, Deva Ramanan:
Pix2Map: Cross-modal Retrieval for Inferring Street Maps from Images. CoRR abs/2301.04224 (2023) - [i114]Zhiqiu Lin, Samuel Yu, Zhiyi Kuang, Deepak Pathak, Deva Ramanan:
Multimodality Helps Unimodality: Cross-Modal Few-Shot Learning with Multimodal Models. CoRR abs/2301.06267 (2023) - [i113]Kangle Deng, Gengshan Yang, Deva Ramanan, Jun-Yan Zhu:
3D-aware Conditional Image Synthesis. CoRR abs/2302.08509 (2023) - [i112]Tarasha Khurana, Peiyun Hu, David Held, Deva Ramanan:
Point Cloud Forecasting as a Proxy for 4D Occupancy Forecasting. CoRR abs/2302.13130 (2023) - [i111]Haithem Turki, Jason Y. Zhang, Francesco Ferroni, Deva Ramanan:
SUDS: Scalable Urban Dynamic Scenes. CoRR abs/2303.14536 (2023) - [i110]Chittesh Thavamani, Mengtian Li, Francesco Ferroni, Deva Ramanan:
Learning to Zoom and Unzoom. CoRR abs/2303.15390 (2023) - [i109]Nathaniel Chodosh, Deva Ramanan, Simon Lucey:
Re-Evaluating LiDAR Scene Flow for Autonomous Driving. CoRR abs/2304.02150 (2023) - [i108]Chonghyuk Song, Gengshan Yang, Kangle Deng, Jun-Yan Zhu, Deva Ramanan:
Total-Recon: Deformable Scene Reconstruction for Embodied View Synthesis. CoRR abs/2304.12317 (2023) - [i107]John Z. Zhang, Shuo Yang, Gengshan Yang, Arun L. Bishop, Deva Ramanan, Zachary Manchester:
SLoMo: A General System for Legged Robot Motion Imitation from Casual Videos. CoRR abs/2304.14389 (2023) - [i106]Amy Lin, Jason Y. Zhang, Deva Ramanan, Shubham Tulsiani:
RelPose++: Recovering 6D Poses from Sparse-view Observations. CoRR abs/2305.04926 (2023) - [i105]Erica Weng, Hana Hoshino, Deva Ramanan, Kris Kitani:
Joint Metrics Matter: A Better Standard for Trajectory Forecasting. CoRR abs/2305.06292 (2023) - [i104]Gengshan Yang, Chaoyang Wang, N. Dinesh Reddy, Deva Ramanan:
Reconstructing Animatable Categories from Videos. CoRR abs/2305.06351 (2023) - [i103]Aboli Marathe, Deva Ramanan, Rahee Walambe, Ketan Kotecha:
WEDGE: A multi-weather autonomous driving dataset built from generative vision-language models. CoRR abs/2305.07528 (2023) - [i102]Kyle Vedder, Neehar Peri, Nathaniel Chodosh, Ishan Khatri, Eric Eaton, Dinesh Jayaraman, Yang Liu, Deva Ramanan, James Hays:
ZeroFlow: Fast Zero Label Scene Flow via Distillation. CoRR abs/2305.10424 (2023) - [i101]Zhiqiu Lin, Xinyue Chen, Deepak Pathak, Pengchuan Zhang, Deva Ramanan:
VisualGPTScore: Visio-Linguistic Reasoning with Multimodal Generative Pre-Training Scores. CoRR abs/2306.01879 (2023) - [i100]Nadine Chang, Francesco Ferroni, Michael J. Tarr, Martial Hebert, Deva Ramanan:
Thinking Like an Annotator: Generation of Dataset Labeling Instructions. CoRR abs/2306.14035 (2023) - [i99]Neehar Peri, Mengtian Li, Benjamin Wilson, Yu-Xiong Wang, James Hays, Deva Ramanan:
An Empirical Analysis of Range for 3D Object Detection. CoRR abs/2308.04054 (2023) - [i98]Shengcao Cao, Mengtian Li, James Hays, Deva Ramanan, Yu-Xiong Wang, Liang-Yan Gui:
Learning Lightweight Object Detectors via Multi-Teacher Progressive Distillation. CoRR abs/2308.09105 (2023) - [i97]Jonathon Luiten, Georgios Kopanas, Bastian Leibe, Deva Ramanan:
Dynamic 3D Gaussians: Tracking by Persistent Dynamic View Synthesis. CoRR abs/2308.09713 (2023) - [i96]Shihong Liu, Samuel Yu, Zhiqiu Lin, Deepak Pathak, Deva Ramanan:
Language Models as Black-Box Optimizers for Vision-Language Models. CoRR abs/2309.05950 (2023) - [i95]Ziqi Pang, Deva Ramanan, Mengtian Li, Yu-Xiong Wang:
Streaming Motion Forecasting for Autonomous Driving. CoRR abs/2310.01351 (2023) - [i94]Erica Weng, Kenta Mukoya, Deva Ramanan, Kris Kitani:
Evaluating a VR System for Collecting Safety-Critical Vehicle-Pedestrian Interactions. CoRR abs/2310.05882 (2023) - [i93]Abhinav Agarwalla, Xuhua Huang, Jason Ziglar, Francesco Ferroni, Laura Leal-Taixé, James Hays, Aljosa Osep, Deva Ramanan:
Lidar Panoptic Segmentation and Tracking without Bells and Whistles. CoRR abs/2310.12464 (2023) - [i92]Haithem Turki, Michael Zollhöfer, Christian Richardt, Deva Ramanan:
PyNeRF: Pyramidal Neural Radiance Fields. CoRR abs/2312.00252 (2023) - [i91]Nikhil Varma Keetha, Jay Karhade, Krishna Murthy Jatavallabhula, Gengshan Yang, Sebastian A. Scherer, Deva Ramanan, Jonathon Luiten:
SplaTAM: Splat, Track & Map 3D Gaussians for Dense RGB-D SLAM. CoRR abs/2312.02126 (2023) - [i90]Haithem Turki, Vasu Agrawal, Samuel Rota Bulò, Lorenzo Porzi, Peter Kontschieder, Deva Ramanan, Michael Zollhöfer, Christian Richardt:
HybridNeRF: Efficient Neural Rendering via Adaptive Volumetric Surfaces. CoRR abs/2312.03160 (2023) - [i89]Yechi Ma, Neehar Peri, Shuoquan Wei, Wei Hua, Deva Ramanan, Yanan Li, Shu Kong:
Long-Tailed 3D Detection via 2D Late Fusion. CoRR abs/2312.10986 (2023) - [i88]Cheng-Yen Hsieh, Tarasha Khurana, Achal Dave, Deva Ramanan:
Tracking Any Object Amodally. CoRR abs/2312.12433 (2023) - [i87]Anish Madan, Neehar Peri, Shu Kong, Deva Ramanan:
Revisiting Few-Shot Object Detection with Vision-Language Models. CoRR abs/2312.14494 (2023) - 2022
- [c132]Neehar Peri, Achal Dave, Deva Ramanan, Shu Kong:
Towards Long-Tailed 3D Detection. CoRL 2022: 1904-1915 - [c131]Gengshan Yang, Minh Vo, Natalia Neverova, Deva Ramanan, Andrea Vedaldi, Hanbyul Joo:
BANMo: Building Animatable 3D Neural Models from Many Casual Videos. CVPR 2022: 2853-2863 - [c130]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. CVPR 2022: 3012-3021 - [c129]Shaden Alshammari, Yu-Xiong Wang, Deva Ramanan, Shu Kong:
Long- Tailed Recognition via Weight Balancing. CVPR 2022: 6887-6897 - [c128]Kangle Deng, Andrew Liu, Jun-Yan Zhu, Deva Ramanan:
Depth-supervised NeRF: Fewer Views and Faster Training for Free. CVPR 2022: 12872-12881 - [c127]Haithem Turki, Deva Ramanan, Mahadev Satyanarayanan:
Mega-NeRF: Scalable Construction of Large-Scale NeRFs for Virtual Fly- Throughs. CVPR 2022: 12912-12921 - [c126]Neehar Peri, Jonathon Luiten, Mengtian Li, Aljosa Osep, Laura Leal-Taixé, Deva Ramanan:
Forecasting from LiDAR via Future Object Detection. CVPR 2022: 17181-17190 - [c125]Yang Liu, Idil Esen Zulfikar, Jonathon Luiten, Achal Dave, Deva Ramanan, Bastian Leibe, Aljosa Osep, Laura Leal-Taixé:
Opening up Open World Tracking. CVPR 2022: 19023-19033 - [c124]Yi-Ting Chen, Jinghao Shi, Zelin Ye, Christoph Mertz, Deva Ramanan, Shu Kong:
Multimodal Object Detection via Probabilistic Ensembling. ECCV (9) 2022: 139-158 - [c123]Tarasha Khurana, Peiyun Hu, Achal Dave, Jason Ziglar, David Held, Deva Ramanan:
Differentiable Raycasting for Self-Supervised Occupancy Forecasting. ECCV (38) 2022: 353-369 - [c122]Jason Y. Zhang, Deva Ramanan, Shubham Tulsiani:
RelPose: Predicting Probabilistic Relative Rotation for Single Objects in the Wild. ECCV (31) 2022: 592-611 - [c121]Vladimir Fomenko, Ismail Elezi, Deva Ramanan, Laura Leal-Taixé, Aljosa Osep:
Learning to Discover and Detect Objects. NeurIPS 2022 - [c120]Zhiqiu Lin, Deepak Pathak, Yu-Xiong Wang, Deva Ramanan, Shu Kong:
Continual Learning with Evolving Class Ontologies. NeurIPS 2022 - [i86]Zhiqiu Lin, Jia Shi, Deepak Pathak, Deva Ramanan:
The CLEAR Benchmark: Continual LEArning on Real-World Imagery. CoRR abs/2201.06289 (2022) - [i85]Shaden Alshammari, Yu-Xiong Wang, Deva Ramanan, Shu Kong:
Long-Tailed Recognition via Weight Balancing. CoRR abs/2203.14197 (2022) - [i84]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) - [i83]Joshua Spisak, Andrew Saba, Nayana Suvarna, Brian Mao, Chuan Tian Zhang, Chris Chang, Sebastian A. Scherer, Deva Ramanan:
Robust Modeling and Controls for Racing on the Edge. CoRR abs/2205.10841 (2022) - [i82]Ali Athar, Jonathon Luiten, Alexander Hermans, Deva Ramanan, Bastian Leibe:
Differentiable Soft-Masked Attention. CoRR abs/2206.00182 (2022) - [i81]Jason Y. Zhang, Deva Ramanan, Shubham Tulsiani:
RelPose: Predicting Probabilistic Relative Rotation for Single Objects in the Wild. CoRR abs/2208.05963 (2022) - [i80]Ali Athar, Jonathon Luiten, Paul Voigtlaender, Tarasha Khurana, Achal Dave, Bastian Leibe, Deva Ramanan:
BURST: A Benchmark for Unifying Object Recognition, Segmentation and Tracking in Video. CoRR abs/2209.12118 (2022) - [i79]Tarasha Khurana, Peiyun Hu, Achal Dave, Jason Ziglar, David Held, Deva Ramanan:
Differentiable Raycasting for Self-supervised Occupancy Forecasting. CoRR abs/2210.01917 (2022) - [i78]Zhiqiu Lin, Deepak Pathak, Yu-Xiong Wang, Deva Ramanan, Shu Kong:
Learning with an Evolving Class Ontology. CoRR abs/2210.04993 (2022) - [i77]Vladimir Fomenko, Ismail Elezi, Deva Ramanan, Laura Leal-Taixé, Aljosa Osep:
Learning to Discover and Detect Objects. CoRR abs/2210.10774 (2022) - [i76]Yang Liu, Shen Yan, Laura Leal-Taixé, James Hays, Deva Ramanan:
Soft Augmentation for Image Classification. CoRR abs/2211.04625 (2022) - [i75]Neehar Peri, Achal Dave, Deva Ramanan, Shu Kong:
Towards Long-Tailed 3D Detection. CoRR abs/2211.08691 (2022) - [i74]Shubham Gupta, Jeet Kanjani, Mengtian Li, Francesco Ferroni, James Hays, Deva Ramanan, Shu Kong:
Far3Det: Towards Far-Field 3D Detection. CoRR abs/2211.13858 (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 Y. 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]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 NREC Agricultural Person-Detection Dataset. CoRR abs/1707.07169 (2017) - [i18]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, Cezary Stankiewicz, Terrance E. Boult:
Unconstrained Face Detection and Open-Set Face Recognition Challenge. CoRR abs/1708.02337 (2017) - [i17]Chen Huang, Simon Lucey, Deva Ramanan:
Learning Policies for Adaptive Tracking with Deep Feature Cascades. CoRR abs/1708.02973 (2017) - [i16]Aayush Bansal, Yaser Sheikh, Deva Ramanan:
PixelNN: Example-based Image Synthesis. CoRR abs/1708.05349 (2017) - [i15]Rohit Girdhar, Deva Ramanan:
Attentional Pooling for Action Recognition. CoRR abs/1711.01467 (2017) - 2016
- [j15]Xiangxin Zhu, Carl Vondrick, Charless C. Fowlkes, Deva Ramanan:
Do We Need More Training Data? Int. J. Comput. Vis. 119(1): 76-92 (2016) - [j14]Ivan Laptev, Deva Ramanan, Josef Sivic:
Guest Editorial: Video Recognition. Int. J. Comput. Vis. 119(3): 217-218 (2016) - [j13]Liyan Zhang, Xikui Wang, Dmitri V. Kalashnikov, Sharad Mehrotra, Deva Ramanan:
Query-Driven Approach to Face Clustering and Tagging. IEEE Trans. Image Process. 25(10): 4504-4513 (2016) - [c58]Peiyun Hu, Deva Ramanan:
Bottom-Up and Top-Down Reasoning with Hierarchical Rectified Gaussians. CVPR 2016: 5600-5609 - [c57]Mohsen Hejrati, Deva Ramanan:
Categorizing cubes: Revisiting pose normalization. WACV 2016: 1-9 - [i14]Phuc Xuan Nguyen, Grégory Rogez, Charless C. Fowlkes, Deva Ramanan:
The Open World of Micro-Videos. CoRR abs/1603.09439 (2016) - [i13]Aayush Bansal, Xinlei Chen, Bryan C. Russell, Abhinav Gupta, Deva Ramanan:
PixelNet: Towards a General Pixel-level Architecture. CoRR abs/1609.06694 (2016) - [i12]Peiyun Hu, Deva Ramanan:
Finding Tiny Faces. CoRR abs/1612.04402 (2016) - [i11]Vivek Krishnan, Deva Ramanan:
Tinkering Under the Hood: Interactive Zero-Shot Learning with Net Surgery. CoRR abs/1612.04901 (2016) - [i10]Ching-Hang Chen, Deva Ramanan:
3D Human Pose Estimation = 2D Pose Estimation + Matching. CoRR abs/1612.06524 (2016) - 2015
- [c56]Dennis Park, Deva Ramanan:
Articulated pose estimation with tiny synthetic videos. CVPR Workshops 2015: 58-66 - [c55]Grégory Rogez, James Steven Supancic III, Deva Ramanan:
First-person pose recognition using egocentric workspaces. CVPR 2015: 4325-4333 - [c54]Songfan Yang, Deva Ramanan:
Multi-scale Recognition with DAG-CNNs. ICCV 2015: 1215-1223 - [c53]James Steven Supancic III, Grégory Rogez, Yi Yang, Jamie Shotton, Deva Ramanan:
Depth-Based Hand Pose Estimation: Data, Methods, and Challenges. ICCV 2015: 1868-1876 - [c52]Chunshui Cao, Xianming Liu, Yi Yang, Yinan Yu, Jiang Wang, Zilei Wang, Yongzhen Huang, Liang Wang, Chang Huang, Wei Xu, Deva Ramanan, Thomas S. Huang:
Look and Think Twice: Capturing Top-Down Visual Attention with Feedback Convolutional Neural Networks. ICCV 2015: 2956-2964 - [c51]Grégory Rogez, James Steven Supancic III, Deva Ramanan:
Understanding Everyday Hands in Action from RGB-D Images. ICCV 2015: 3889-3897 - [i9]Xiangxin Zhu, Carl Vondrick, Charless C. Fowlkes, Deva Ramanan:
Do We Need More Training Data? CoRR abs/1503.01508 (2015) - [i8]James Steven Supancic III, Grégory Rogez, Yi Yang, Jamie Shotton, Deva Ramanan:
Depth-based hand pose estimation: methods, data, and challenges. CoRR abs/1504.06378 (2015) - [i7]Songfan Yang, Deva Ramanan:
Multi-scale recognition with DAG-CNNs. CoRR abs/1505.05232 (2015) - [i6]Peiyun Hu, Deva Ramanan:
Bottom-up and top-down reasoning with convolutional latent-variable models. CoRR abs/1507.05699 (2015) - 2014
- [j12]Ronen Vaisenberg, Alessio Della Motta, Sharad Mehrotra, Deva Ramanan:
Scheduling sensors for monitoring sentient spaces using an approximate POMDP policy. Pervasive Mob. Comput. 10: 83-103 (2014) - [c50]Hamed Pirsiavash, Deva Ramanan:
Parsing Videos of Actions with Segmental Grammars. CVPR 2014: 612-619 - [c49]Xiangxin Zhu, Dragomir Anguelov, Deva Ramanan:
Capturing Long-Tail Distributions of Object Subcategories. CVPR 2014: 915-922 - [c48]Golnaz Ghiasi, Yi Yang, Deva Ramanan, Charless C. Fowlkes:
Parsing Occluded People. CVPR 2014: 2401-2408 - [c47]Mohsen Hejrati, Deva Ramanan:
Analysis by Synthesis: 3D Object Recognition by Object Reconstruction. CVPR 2014: 2449-2456 - [c46]Grégory Rogez, Maryam Khademi, James Steven Supancic III, J. M. M. Montiel, Deva Ramanan:
3D Hand Pose Detection in Egocentric RGB-D Images. ECCV Workshops (1) 2014: 356-371 - [c45]Tsung-Yi Lin, Michael Maire, Serge J. Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, C. Lawrence Zitnick:
Microsoft COCO: Common Objects in Context. ECCV (5) 2014: 740-755 - [c44]Krishnan Ramnath, Simon Baker, Lucy Vanderwende, Motaz Ahmad El-Saban, Sudipta N. Sinha, Anitha Kannan, Noran Hassan, Michel Galley, Yi Yang, Deva Ramanan, Alessandro Bergamo, Lorenzo Torresani:
AutoCaption: Automatic caption generation for personal photos. WACV 2014: 1050-1057 - [i5]Tsung-Yi Lin, Michael Maire, Serge J. Belongie, Lubomir D. Bourdev, Ross B. Girshick, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, C. Lawrence Zitnick:
Microsoft COCO: Common Objects in Context. CoRR abs/1405.0312 (2014) - [i4]Grégory Rogez, James Steven Supancic III, Deva Ramanan:
Egocentric Pose Recognition in Four Lines of Code. CoRR abs/1412.0060 (2014) - [i3]Grégory Rogez, James Steven Supancic III, Maryam Khademi, José María Martínez Montiel, Deva Ramanan:
3D Hand Pose Detection in Egocentric RGB-D Images. CoRR abs/1412.0065 (2014) - 2013
- [j11]Pedro F. Felzenszwalb, Ross B. Girshick, David A. McAllester, Deva Ramanan:
Visual object detection with deformable part models. Commun. ACM 56(9): 97-105 (2013) - [j10]Carl Vondrick, Donald J. Patterson, Deva Ramanan:
Efficiently Scaling up Crowdsourced Video Annotation - A Set of Best Practices for High Quality, Economical Video Labeling. Int. J. Comput. Vis. 101(1): 184-204 (2013) - [j9]Yi Yang, Deva Ramanan:
Articulated Human Detection with Flexible Mixtures of Parts. IEEE Trans. Pattern Anal. Mach. Intell. 35(12): 2878-2890 (2013) - [c43]Chaitanya Desai, Deva Ramanan:
Predicting Functional Regions on Objects. CVPR Workshops 2013: 968-975 - [c42]James Steven Supancic III, Deva Ramanan:
Self-Paced Learning for Long-Term Tracking. CVPR 2013: 2379-2386 - [c41]Dennis Park, C. Lawrence Zitnick, Deva Ramanan, Piotr Dollár:
Exploring Weak Stabilization for Motion Feature Extraction. CVPR 2013: 2882-2889 - [c40]Xiaofeng Ren, Deva Ramanan:
Histograms of Sparse Codes for Object Detection. CVPR 2013: 3246-3253 - [c39]Ronen Vaisenberg, Alessio Della Motta, Sharad Mehrotra, Deva Ramanan:
Scheduling sensors for monitoring sentient spaces using an approximate POMDP policy. PerCom 2013: 141-150 - [i2]Deva Ramanan:
Dual coordinate solvers for large-scale structural SVMs. CoRR abs/1312.1743 (2013) - [i1]Grégory Rogez, Deva Ramanan, J. M. M. Montiel:
Egovision4Health - Assessing Activities of Daily Living from a Wearable RGB-D Camera for In-Home Health Care Applications. ERCIM News 2013(95) (2013) - 2012
- [j8]Yi Yang, Sam Hallman, Deva Ramanan, Charless C. Fowlkes:
Layered Object Models for Image Segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 34(9): 1731-1743 (2012) - [c38]Xiangxin Zhu, Carl Vondrick, Deva Ramanan, Charless C. Fowlkes:
Do We Need More Training Data or Better Models for Object Detection?. BMVC 2012: 1-11 - [c37]Hamed Pirsiavash, Deva Ramanan:
Detecting activities of daily living in first-person camera views. CVPR 2012: 2847-2854 - [c36]Xiangxin Zhu, Deva Ramanan:
Face detection, pose estimation, and landmark localization in the wild. CVPR 2012: 2879-2886 - [c35]Hamed Pirsiavash, Deva Ramanan:
Steerable part models. CVPR 2012: 3226-3233 - [c34]Yi Yang, Simon Baker, Anitha Kannan, Deva Ramanan:
Recognizing proxemics in personal photos. CVPR 2012: 3522-3529 - [c33]Chaitanya Desai, Deva Ramanan:
Detecting Actions, Poses, and Objects with Relational Phraselets. ECCV (4) 2012: 158-172 - [c32]Bharath Hariharan, Jitendra Malik, Deva Ramanan:
Discriminative Decorrelation for Clustering and Classification. ECCV (4) 2012: 459-472 - [c31]Mohsen Hejrati, Deva Ramanan:
Analyzing 3D Objects in Cluttered Images. NIPS 2012: 602-610 - 2011
- [j7]Chaitanya Desai, Deva Ramanan, Charless C. Fowlkes:
Discriminative Models for Multi-Class Object Layout. Int. J. Comput. Vis. 95(1): 1-12 (2011) - [j6]Deva Ramanan, Simon Baker:
Local Distance Functions: A Taxonomy, New Algorithms, and an Evaluation. IEEE Trans. Pattern Anal. Mach. Intell. 33(4): 794-806 (2011) - [c30]Sangmin Oh, Anthony Hoogs, A. G. Amitha Perera, Naresh P. Cuntoor, Chia-Chih Chen, Jong Taek Lee, Saurajit Mukherjee, J. K. Aggarwal, Hyungtae Lee, Larry S. Davis, Eran Swears, Xiaoyang Wang, Qiang Ji, Kishore K. Reddy, Mubarak Shah, Carl Vondrick, Hamed Pirsiavash, Deva Ramanan, Jenny Yuen, Antonio Torralba, Bi Song, Anesco Fong, Amit K. Roy-Chowdhury, Mita Desai:
AVSS 2011 demo session: A large-scale benchmark dataset for event recognition in surveillance video. AVSS 2011: 527-528 - [c29]Hamed Pirsiavash, Deva Ramanan, Charless C. Fowlkes:
Globally-optimal greedy algorithms for tracking a variable number of objects. CVPR 2011: 1201-1208 - [c28]Yi Yang, Deva Ramanan:
Articulated pose estimation with flexible mixtures-of-parts. CVPR 2011: 1385-1392 - [c27]Rahul Garg, Steven M. Seitz, Deva Ramanan, Noah Snavely:
Where's Waldo: Matching people in images of crowds. CVPR 2011: 1793-1800 - [c26]Sangmin Oh, Anthony Hoogs, A. G. Amitha Perera, Naresh P. Cuntoor, Chia-Chih Chen, Jong Taek Lee, Saurajit Mukherjee, J. K. Aggarwal, Hyungtae Lee, Larry S. Davis, Eran Swears, Xiaoyang Wang, Qiang Ji, Kishore K. Reddy, Mubarak Shah, Carl Vondrick, Hamed Pirsiavash, Deva Ramanan, Jenny Yuen, Antonio Torralba, Bi Song, Anesco Fong, Amit K. Roy-Chowdhury, Mita Desai:
A large-scale benchmark dataset for event recognition in surveillance video. CVPR 2011: 3153-3160 - [c25]Dennis Park, Deva Ramanan:
N-best maximal decoders for part models. ICCV 2011: 2627-2634 - [c24]Carl Vondrick, Deva Ramanan:
Video Annotation and Tracking with Active Learning. NIPS 2011: 28-36 - [c23]Levi Boyles, Anoop Korattikara Balan, Deva Ramanan, Max Welling:
Statistical Tests for Optimization Efficiency. NIPS 2011: 2196-2204 - [p1]Deva Ramanan:
Part-Based Models for Finding People and Estimating Their Pose. Visual Analysis of Humans 2011: 199-223 - 2010
- [j5]Ronen Vaisenberg, Sharad Mehrotra, Deva Ramanan:
SEMARTCam scheduler: semantics driven real-time data collection from indoor camera networks to maximize event detection. J. Real Time Image Process. 5(4): 215-230 (2010) - [j4]Pedro F. Felzenszwalb, Ross B. Girshick, David A. McAllester, Deva Ramanan:
Object Detection with Discriminatively Trained Part-Based Models. IEEE Trans. Pattern Anal. Mach. Intell. 32(9): 1627-1645 (2010) - [c22]Chaitanya Desai, Deva Ramanan, Charless C. Fowlkes:
Discriminative models for static human-object interactions. CVPR Workshops 2010: 9-16 - [c21]Yi Yang, Sam Hallman, Deva Ramanan, Charless C. Fowlkes:
Layered object detection for multi-class segmentation. CVPR 2010: 3113-3120 - [c20]Dennis Park, Deva Ramanan, Charless C. Fowlkes:
Multiresolution Models for Object Detection. ECCV (4) 2010: 241-254 - [c19]Carl Vondrick, Deva Ramanan, Donald J. Patterson:
Efficiently Scaling Up Video Annotation with Crowdsourced Marketplaces. ECCV (4) 2010: 610-623 - [c18]Pedro F. Felzenszwalb, Ross B. Girshick, David A. McAllester, Deva Ramanan:
Discriminative Latent Variable Models for Object Detection. ICML 2010: 11-12
2000 – 2009
- 2009
- [c17]Chaitanya Desai, Deva Ramanan, Charless C. Fowlkes:
Discriminative models for multi-class object layout. ICCV 2009: 229-236 - [c16]Deva Ramanan, Simon Baker:
Local distance functions: A taxonomy, new algorithms, and an evaluation. ICCV 2009: 301-308 - [c15]Hamed Pirsiavash, Deva Ramanan, Charless C. Fowlkes:
Bilinear classifiers for visual recognition. NIPS 2009: 1482-1490 - 2008
- [c14]Pedro F. Felzenszwalb, David A. McAllester, Deva Ramanan:
A discriminatively trained, multiscale, deformable part model. CVPR 2008 - [c13]Krishnan Ramnath, Simon Baker, Iain A. Matthews, Deva Ramanan:
Increasing the density of Active Appearance Models. CVPR 2008 - 2007
- [j3]Deva Ramanan, David A. Forsyth, Andrew Zisserman:
Tracking People by Learning Their Appearance. IEEE Trans. Pattern Anal. Mach. Intell. 29(1): 65-81 (2007) - [c12]Deva Ramanan:
Using Segmentation to Verify Object Hypotheses. CVPR 2007 - [c11]Deva Ramanan, Simon Baker, Sham M. Kakade:
Leveragingarchivalvideo for building face datasets. ICCV 2007: 1-8 - [c10]Sonya Allin, Deva Ramanan:
Assessment of Post-Stroke Functioning Using Machine Vision. MVA 2007: 299-302 - 2006
- [j2]Deva Ramanan, David A. Forsyth, Kobus Barnard:
Building Models of Animals from Video. IEEE Trans. Pattern Anal. Mach. Intell. 28(8): 1319-1334 (2006) - [c9]Deva Ramanan, Cristian Sminchisescu:
Training Deformable Models for Localization. CVPR (1) 2006: 206-213 - [c8]Deva Ramanan:
Learning to parse images of articulated bodies. NIPS 2006: 1129-1136 - 2005
- [j1]David A. Forsyth, Okan Arikan, Leslie Ikemoto, James F. O'Brien, Deva Ramanan:
Computational Studies of Human Motion: Part 1, Tracking and Motion Synthesis. Found. Trends Comput. Graph. Vis. 1(2/3) (2005) - [c7]Deva Ramanan, David A. Forsyth, Andrew Zisserman:
Strike a Pose: Tracking People by Finding Stylized Poses. CVPR (1) 2005: 271-278 - [c6]Deva Ramanan, David A. Forsyth, Kobus Barnard:
Detecting, Localizing and Recovering Kinematics of Textured Animals. CVPR (2) 2005: 635-642 - [c5]Deva Ramanan, David A. Forsyth, Andrew Zisserman:
Tracking People and Recognizing Their Activities. CVPR (2) 2005: 1194 - 2003
- [c4]Deva Ramanan, David A. Forsyth:
Finding and Tracking People from the Bottom Up. CVPR (2) 2003: 467-474 - [c3]Deva Ramanan, David A. Forsyth:
Using Temporal Coherence to Build Models of Animals. ICCV 2003: 338-345 - [c2]Deva Ramanan, David A. Forsyth:
Automatic Annotation of Everyday Movements. NIPS 2003: 1547-1554 - 2000
- [c1]Deva Ramanan, Kenneth E. Barner:
Nonlinear Image Interpolation Through Extended Permutation Filters. ICIP 2000: 912-915
Coauthor Index
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