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2020 – today
- 2024
[c22]João Carreira, Michael King, Viorica Patraucean, Dilara Gokay, Catalin Ionescu, Yi Yang, Daniel Zoran, Joseph Heyward, Carl Doersch, Yusuf Aytar, Dima Damen, Andrew Zisserman:
Learning from One Continuous Video Stream. CVPR 2024: 28751-28761- [c21]Mel Vecerík, Carl Doersch, Yi Yang, Todor Davchev, Yusuf Aytar, Guangyao Zhou, Raia Hadsell, Lourdes Agapito, Jon Scholz:
RoboTAP: Tracking Arbitrary Points for Few-Shot Visual Imitation. ICRA 2024: 5397-5403 - [i28]Carl Doersch, Yi Yang, Dilara Gokay, Pauline Luc, Skanda Koppula, Ankush Gupta, Joseph Heyward, Ross Goroshin, João Carreira, Andrew Zisserman:
BootsTAP: Bootstrapped Training for Tracking-Any-Point. CoRR abs/2402.00847 (2024) - [i27]Skanda Koppula, Ignacio Rocco, Yi Yang, Joseph Heyward, João Carreira, Andrew Zisserman, Gabriel Brostow, Carl Doersch:
TAPVid-3D: A Benchmark for Tracking Any Point in 3D. CoRR abs/2407.05921 (2024) - [i26]Homanga Bharadhwaj, Debidatta Dwibedi, Abhinav Gupta, Shubham Tulsiani, Carl Doersch, Ted Xiao, Dhruv Shah, Fei Xia, Dorsa Sadigh, Sean Kirmani:
Gen2Act: Human Video Generation in Novel Scenarios enables Generalizable Robot Manipulation. CoRR abs/2409.16283 (2024) - 2023
- [c20]Carl Doersch, Yi Yang, Mel Vecerík, Dilara Gokay, Ankush Gupta, Yusuf Aytar, João Carreira, Andrew Zisserman:
TAPIR: Tracking Any Point with per-frame Initialization and temporal Refinement. ICCV 2023: 10027-10038 - [c19]Viorica Patraucean, Lucas Smaira, Ankush Gupta, Adrià Recasens, Larisa Markeeva, Dylan Banarse, Skanda Koppula, Joseph Heyward, Mateusz Malinowski, Yi Yang, Carl Doersch, Tatiana Matejovicova, Yury Sulsky, Antoine Miech, Alexandre Fréchette, Hanna Klimczak, Raphael Koster, Junlin Zhang, Stephanie Winkler, Yusuf Aytar, Simon Osindero, Dima Damen, Andrew Zisserman, João Carreira:
Perception Test: A Diagnostic Benchmark for Multimodal Video Models. NeurIPS 2023 - [i25]Viorica Patraucean, Lucas Smaira, Ankush Gupta, Adrià Recasens Continente, Larisa Markeeva, Dylan Banarse, Skanda Koppula, Joseph Heyward, Mateusz Malinowski, Yi Yang, Carl Doersch, Tatiana Matejovicova, Yury Sulsky, Antoine Miech, Alexandre Fréchette, Hanna Klimczak, Raphael Koster, Junlin Zhang, Stephanie Winkler, Yusuf Aytar, Simon Osindero, Dima Damen, Andrew Zisserman, João Carreira:
Perception Test: A Diagnostic Benchmark for Multimodal Video Models. CoRR abs/2305.13786 (2023) - [i24]Carl Doersch, Yi Yang, Mel Vecerík, Dilara Gokay, Ankush Gupta, Yusuf Aytar, João Carreira, Andrew Zisserman:
TAPIR: Tracking Any Point with per-frame Initialization and temporal Refinement. CoRR abs/2306.08637 (2023) - [i23]Mel Vecerík, Carl Doersch, Yi Yang, Todor Davchev, Yusuf Aytar, Guangyao Zhou, Raia Hadsell, Lourdes Agapito, Jon Scholz:
RoboTAP: Tracking Arbitrary Points for Few-Shot Visual Imitation. CoRR abs/2308.15975 (2023) - [i22]João Carreira, Michael King, Viorica Patraucean, Dilara Gokay, Catalin Ionescu, Yi Yang, Daniel Zoran, Joseph Heyward, Carl Doersch, Yusuf Aytar, Dima Damen, Andrew Zisserman:
Learning from One Continuous Video Stream. CoRR abs/2312.00598 (2023) - 2022
- [c18]Klaus Greff, Francois Belletti, Lucas Beyer, Carl Doersch, Yilun Du, Daniel Duckworth, David J. Fleet, Dan Gnanapragasam, Florian Golemo, Charles Herrmann, Thomas Kipf, Abhijit Kundu, Dmitry Lagun, Issam H. Laradji, Hsueh-Ti Derek Liu, Henning Meyer, Yishu Miao, Derek Nowrouzezahrai, A. Cengiz Öztireli, Etienne Pot, Noha Radwan, Daniel Rebain, Sara Sabour, Mehdi S. M. Sajjadi, Matan Sela, Vincent Sitzmann, Austin Stone, Deqing Sun, Suhani Vora, Ziyu Wang, Tianhao Wu, Kwang Moo Yi, Fangcheng Zhong, Andrea Tagliasacchi:
Kubric: A scalable dataset generator. CVPR 2022: 3739-3751 - [c17]Wang Yifan
, Carl Doersch, Relja Arandjelovic, João Carreira, Andrew Zisserman:
Input-level Inductive Biases for 3D Reconstruction. CVPR 2022: 6166-6176 - [c16]Andrew Jaegle, Sebastian Borgeaud, Jean-Baptiste Alayrac, Carl Doersch, Catalin Ionescu, David Ding, Skanda Koppula, Daniel Zoran, Andrew Brock, Evan Shelhamer, Olivier J. Hénaff, Matthew M. Botvinick, Andrew Zisserman, Oriol Vinyals, João Carreira:
Perceiver IO: A General Architecture for Structured Inputs & Outputs. ICLR 2022 - [c15]Carl Doersch, Ankush Gupta, Larisa Markeeva, Adrià Recasens, Lucas Smaira, Yusuf Aytar, João Carreira, Andrew Zisserman, Yi Yang:
TAP-Vid: A Benchmark for Tracking Any Point in a Video. NeurIPS 2022 - [i21]Klaus Greff, Francois Belletti, Lucas Beyer, Carl Doersch, Yilun Du, Daniel Duckworth, David J. Fleet, Dan Gnanapragasam, Florian Golemo, Charles Herrmann, Thomas Kipf, Abhijit Kundu, Dmitry Lagun, Issam H. Laradji, Hsueh-Ti Derek Liu, Henning Meyer, Yishu Miao, Derek Nowrouzezahrai, Cengiz Öztireli, Etienne Pot, Noha Radwan, Daniel Rebain, Sara Sabour, Mehdi S. M. Sajjadi, Matan Sela, Vincent Sitzmann, Austin Stone, Deqing Sun, Suhani Vora, Ziyu Wang, Tianhao Wu, Kwang Moo Yi, Fangcheng Zhong, Andrea Tagliasacchi:
Kubric: A scalable dataset generator. CoRR abs/2203.03570 (2022) - [i20]Carl Doersch, Ankush Gupta, Larisa Markeeva, Adrià Recasens, Lucas Smaira, Yusuf Aytar, João Carreira, Andrew Zisserman, Yi Yang:
TAP-Vid: A Benchmark for Tracking Any Point in a Video. CoRR abs/2211.03726 (2022) - 2021
- [i19]Dan Rosenbaum, Marta Garnelo, Michal Zielinski, Charlie Beattie, Ellen Clancy, Andrea Huber, Pushmeet Kohli, Andrew W. Senior, John Jumper, Carl Doersch, S. M. Ali Eslami, Olaf Ronneberger, Jonas Adler:
Inferring a Continuous Distribution of Atom Coordinates from Cryo-EM Images using VAEs. CoRR abs/2106.14108 (2021) - [i18]Andrew Jaegle, Sebastian Borgeaud, Jean-Baptiste Alayrac, Carl Doersch, Catalin Ionescu, David Ding, Skanda Koppula, Daniel Zoran, Andrew Brock, Evan Shelhamer, Olivier J. Hénaff, Matthew M. Botvinick, Andrew Zisserman, Oriol Vinyals, João Carreira:
Perceiver IO: A General Architecture for Structured Inputs & Outputs. CoRR abs/2107.14795 (2021) - [i17]Wang Yifan, Carl Doersch, Relja Arandjelovic, João Carreira, Andrew Zisserman:
Input-level Inductive Biases for 3D Reconstruction. CoRR abs/2112.03243 (2021) - 2020
- [c14]Carl Doersch, Ankush Gupta, Andrew Zisserman:
CrossTransformers: spatially-aware few-shot transfer. NeurIPS 2020 - [c13]Jean-Bastien Grill, Florian Strub, Florent Altché, Corentin Tallec, Pierre H. Richemond, Elena Buchatskaya, Carl Doersch, Bernardo Ávila Pires, Zhaohan Guo, Mohammad Gheshlaghi Azar, Bilal Piot, Koray Kavukcuoglu, Rémi Munos, Michal Valko:
Bootstrap Your Own Latent - A New Approach to Self-Supervised Learning. NeurIPS 2020 - [i16]Jean-Bastien Grill, Florian Strub, Florent Altché, Corentin Tallec, Pierre H. Richemond, Elena Buchatskaya, Carl Doersch, Bernardo Ávila Pires, Zhaohan Daniel Guo, Mohammad Gheshlaghi Azar, Bilal Piot, Koray Kavukcuoglu, Rémi Munos, Michal Valko:
Bootstrap Your Own Latent: A New Approach to Self-Supervised Learning. CoRR abs/2006.07733 (2020) - [i15]Carl Doersch, Ankush Gupta, Andrew Zisserman:
CrossTransformers: spatially-aware few-shot transfer. CoRR abs/2007.11498 (2020)
2010 – 2019
- 2019
- [c12]Rohit Girdhar, João Carreira, Carl Doersch, Andrew Zisserman:
Video Action Transformer Network. CVPR 2019: 244-253 - [c11]Anurag Arnab, Carl Doersch, Andrew Zisserman:
Exploiting Temporal Context for 3D Human Pose Estimation in the Wild. CVPR 2019: 3395-3404 - [c10]Victor Bapst, Alvaro Sanchez-Gonzalez, Carl Doersch, Kimberly L. Stachenfeld, Pushmeet Kohli, Peter W. Battaglia, Jessica B. Hamrick:
Structured agents for physical construction. ICML 2019: 464-474 - [c9]Carl Doersch, Andrew Zisserman:
Sim2real transfer learning for 3D human pose estimation: motion to the rescue. NeurIPS 2019: 12929-12941 - [i14]Victor Bapst, Alvaro Sanchez-Gonzalez, Carl Doersch, Kimberly L. Stachenfeld, Pushmeet Kohli, Peter W. Battaglia, Jessica B. Hamrick:
Structured agents for physical construction. CoRR abs/1904.03177 (2019) - [i13]Anurag Arnab, Carl Doersch, Andrew Zisserman:
Exploiting temporal context for 3D human pose estimation in the wild. CoRR abs/1905.04266 (2019) - [i12]Olivier J. Hénaff, Aravind Srinivas, Jeffrey De Fauw, Ali Razavi, Carl Doersch, S. M. Ali Eslami, Aäron van den Oord:
Data-Efficient Image Recognition with Contrastive Predictive Coding. CoRR abs/1905.09272 (2019) - [i11]Carl Doersch, Andrew Zisserman:
Sim2real transfer learning for 3D pose estimation: motion to the rescue. CoRR abs/1907.02499 (2019) - 2018
- [c8]Mateusz Malinowski, Carl Doersch, Adam Santoro, Peter W. Battaglia:
Learning Visual Question Answering by Bootstrapping Hard Attention. ECCV (6) 2018: 3-20 - [i10]Simon Schmitt, Jonathan J. Hudson, Augustin Zídek, Simon Osindero, Carl Doersch, Wojciech M. Czarnecki, Joel Z. Leibo, Heinrich Küttler, Andrew Zisserman, Karen Simonyan, S. M. Ali Eslami:
Kickstarting Deep Reinforcement Learning. CoRR abs/1803.03835 (2018) - [i9]Rohit Girdhar, João Carreira, Carl Doersch, Andrew Zisserman:
A Better Baseline for AVA. CoRR abs/1807.10066 (2018) - [i8]Mateusz Malinowski, Carl Doersch, Adam Santoro, Peter W. Battaglia:
Learning Visual Question Answering by Bootstrapping Hard Attention. CoRR abs/1808.00300 (2018) - [i7]Mateusz Malinowski, Carl Doersch:
The Visual QA Devil in the Details: The Impact of Early Fusion and Batch Norm on CLEVR. CoRR abs/1809.04482 (2018) - [i6]Rohit Girdhar, João Carreira, Carl Doersch, Andrew Zisserman:
Video Action Transformer Network. CoRR abs/1812.02707 (2018) - 2017
- [c7]Carl Doersch, Andrew Zisserman:
Multi-task Self-Supervised Visual Learning. ICCV 2017: 2070-2079 - [i5]Carl Doersch, Andrew Zisserman:
Multi-task Self-Supervised Visual Learning. CoRR abs/1708.07860 (2017) - 2016
- [b1]Carl Doersch:
Supervision Beyond Manual Annotations for Learning Visual Representations. Carnegie Mellon University, USA, 2016 - [c6]Jacob Walker, Carl Doersch, Abhinav Gupta, Martial Hebert:
An Uncertain Future: Forecasting from Static Images Using Variational Autoencoders. ECCV (7) 2016: 835-851 - [c5]Philipp Krähenbühl, Carl Doersch, Jeff Donahue, Trevor Darrell:
Data-dependent Initializations of Convolutional Neural Networks. ICLR (Poster) 2016 - [i4]Carl Doersch:
Tutorial on Variational Autoencoders. CoRR abs/1606.05908 (2016) - [i3]Jacob Walker, Carl Doersch, Abhinav Gupta, Martial Hebert:
An Uncertain Future: Forecasting from Static Images using Variational Autoencoders. CoRR abs/1606.07873 (2016) - 2015
- [j3]Carl Doersch, Saurabh Singh, Abhinav Gupta, Josef Sivic, Alexei A. Efros:
What makes Paris look like Paris? Commun. ACM 58(12): 103-110 (2015) - [c4]Carl Doersch, Abhinav Gupta, Alexei A. Efros:
Unsupervised Visual Representation Learning by Context Prediction. ICCV 2015: 1422-1430 - [i2]Aayush Bansal, Abhinav Shrivastava, Carl Doersch, Abhinav Gupta:
Mid-level Elements for Object Detection. CoRR abs/1504.07284 (2015) - [i1]Carl Doersch, Abhinav Gupta, Alexei A. Efros:
Unsupervised Visual Representation Learning by Context Prediction. CoRR abs/1505.05192 (2015) - 2014
- [c3]Carl Doersch, Abhinav Gupta, Alexei A. Efros:
Context as Supervisory Signal: Discovering Objects with Predictable Context. ECCV (3) 2014: 362-377 - 2013
- [c2]Carl Doersch, Abhinav Gupta, Alexei A. Efros:
Mid-level Visual Element Discovery as Discriminative Mode Seeking. NIPS 2013: 494-502 - 2012
- [j2]Gary B. Huang, Andrew Kae, Carl Doersch, Erik G. Learned-Miller:
Bounding the Probability of Error for High Precision Optical Character Recognition. J. Mach. Learn. Res. 13: 363-387 (2012) - [j1]Carl Doersch, Saurabh Singh, Abhinav Gupta, Josef Sivic, Alexei A. Efros:
What makes Paris look like Paris? ACM Trans. Graph. 31(4): 101:1-101:9 (2012) - 2010
- [c1]Andrew Kae, Gary B. Huang, Carl Doersch, Erik G. Learned-Miller:
Improving state-of-the-art OCR through high-precision document-specific modeling. CVPR 2010: 1935-1942
Coauthor Index
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last updated on 2024-10-17 20:30 CEST by the dblp team
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