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Most state-of-the-art point trackers are trained on synthetic data due to the difficulty of annotating real videos for this task.
Learning invariance from transformation sequences
Peter Földiák · 1991
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Good features to track
Jianbo Shi and Carlo Tomasi · 1994
Earlier work this paper cites.
Object recognition from local scale-invariant features
David G Lowe · 1999
Earlier work this paper cites.
Slow feature analysis: Unsupervised learning of invariances
Laurenz Wiskott and Terrence J Sejnowski · 2002
Earlier work this paper cites.
Particle video: Long-range motion estimation using point trajectories
Peter Sand and Seth Teller · 2008
Earlier work this paper cites.
Unsupervised learning of spatiotemporally coherent metrics
Ross Goroshin, Joan Bruna, Jonathan Tompson, David Eigen, and Yann LeCun · 2015
Earlier work this paper cites.
Unsupervised learning of visual representations using videos
Xiaolong Wang and Abhinav Gupta · 2015
Earlier work this paper cites.
A benchmark dataset and evaluation methodology for video object segmentation
F. Perazzi, J. Pont-Tuset, B. McWilliams, L. Van Gool, M. Gross, and A. Sorkine-Hornung · 2016
Earlier work this paper cites.
Quo vadis, action recognition? a new model and the kinetics dataset
João Carreira and Andrew Zisserman · 2017
Earlier work this paper cites.
Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2017
Earlier work this paper cites.
Superpoint: Self-supervised interest point detection and description, 2018
Daniel DeTone, Tomasz Malisiewicz, and Andrew Rabinovich · 2018
Earlier work this paper cites.
Unsupervised learning of multi-frame optical flow with occlusions
Joel Janai, Fatma Guney, Anurag Ranjan, Michael Black, and Andreas Geiger · 2018
Earlier work this paper cites.
Unflow: Unsupervised learning of optical flow with a bidirectional census loss
Simon Meister, Junhwa Hur, and Stefan Roth · 2018
Earlier work this paper cites.
Tracking emerges by colorizing videos
Carl Vondrick, Abhinav Shrivastava, Alireza Fathi, Sergio Guadarrama, and Kevin Murphy · 2018
Cited alongside, same era.
Occlusion aware unsupervised learning of optical flow
Yang Wang, Yi Yang, Zhenheng Yang, Liang Zhao, Peng Wang, and Wei Xu · 2018
Cited alongside, same era.
PyTorch Lightning, 2019
William Falcon and The PyTorch Lightning team · 2019
Cited alongside, same era.
Learning correspondence from the cycle-consistency of time
Xiaolong Wang, Allan Jabri, and Alexei A Efros · 2019
Cited alongside, same era.
End-to-end object detection with transformers
Nicolas Carion, Francisco Massa, Gabriel Synnaeve, Nicolas Usunier, Alexander Kirillov, and Sergey Zagoruyko · 2020
Cited alongside, same era.
Space-time correspondence as a contrastive random walk
Allan Jabri, Andrew Owens, and Alexei Efros · 2020
Cited alongside, same era.
Particle video revisited: Tracking through occlusions using point trajectories
Adam W Harley, Zhaoyuan Fang, and Katerina Fragkiadaki · 2022
Later among the works it cites.
Pointodyssey: A large-scale synthetic dataset for long-term point tracking
Yang Zheng, Adam W Harley, Bokui Shen, Gordon Wetzstein, and Leonidas J Guibas · 2022
Later among the works it cites.
TAPIR: Tracking any point with per-frame initialization and temporal refinement
Carl Doersch, Yi Yang, Mel Vecerik, Dilara Gokay, Ankush Gupta, Yusuf Aytar, Joao Carreira, and Andrew Zisserman · 2023
Later among the works it cites.
Dynamicstereo: Consistent dynamic depth from stereo videos
Nikita Karaev, Ignacio Rocco, Benjamin Graham, Natalia Neverova, Andrea Vedaldi, and Christian Rupprecht · 2023
Later among the works it cites.
Lightglue: Local feature matching at light speed, 2023
Philipp Lindenberger, Paul-Edouard Sarlin, and Marc Pollefeys · 2023
Later among the works it cites.
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Mast: A memory-augmented self-supervised tracker
Zihang Lai, Erika Lu, and Weidi Xie · 2020
Cited alongside, same era.
Pytorch distributed: Experiences on accelerating data parallel training, 2020
Shen Li, Yanli Zhao, Rohan Varma, Omkar Salpekar, Pieter Noordhuis, Teng Li, Adam Paszke, Jeff Smith, Brian Vaughan, Pritam Damania, and Soumith Chintala · 2020
Cited alongside, same era.
Learning by analogy: Reliable supervision from transformations for unsupervised optical flow estimation
Liang Liu, Jiangning Zhang, Ruifei He, Yong Liu, Yabiao Wang, Ying Tai, Donghao Luo, Chengjie Wang, Jilin Li, and Feiyue Huang · 2020
Cited alongside, same era.
Raft: Recurrent all-pairs field transforms for optical flow
Zachary Teed and Jia Deng · 2020
Cited alongside, same era.
Disk: Learning local features with policy gradient, 2020
Michał J. Tyszkiewicz, Pascal Fua, and Eduard Trulls · 2020
Cited alongside, same era.
Tap-vid: A benchmark for tracking any point in a video
Carl Doersch, Ankush Gupta, Larisa Markeeva, Adrià Recasens, Lucas Smaira, Yusuf Aytar, João Carreira, Andrew Zisserman, and Yi Yang · 2022
Cited alongside, same era.
Mel Vecerik, Carl Doersch, Yi Yang, Todor Davchev, Yusuf Aytar, Guangyao Zhou, Raia Hadsell, Lourdes Agapito, and Jon Scholz · 2023
Later among the works it cites.
Local all-pair correspondence for point tracking
Seokju Cho, Jiahui Huang, Jisu Nam, Honggyu An, Seungryong Kim, and Joon-Young Lee · 2024
Closest in time.
Bootstap: Bootstrapped training for tracking-any-point
Carl Doersch, Yi Yang, Dilara Gokay, Pauline Luc, Skanda Koppula, Ankush Gupta, Joseph Heyward, Ross Goroshin, João Carreira, and Andrew Zisserman · 2024
Closest in time.
Cotracker: It is better to track together
Nikita Karaev, Ignacio Rocco, Benjamin Graham, Natalia Neverova, Andrea Vedaldi, and Christian Rupprecht · 2024
Closest in time.
Dense optical tracking: Connecting the dots
Guillaume Le Moing, Jean Ponce, and Cordelia Schmid · 2024
Closest in time.
Taptr: Tracking any point with transformers as detection
Hongyang Li, Hao Zhang, Shilong Liu, Zhaoyang Zeng, Tianhe Ren, Feng Li, and Lei Zhang · 2024
Closest in time.
Refining pre-trained motion models
Xinglong Sun, Adam W Harley, and Leonidas J Guibas · 2024
Closest in time.
Vggsfm: Visual geometry grounded deep structure from motion
Jianyuan Wang, Nikita Karaev, Christian Rupprecht, and David Novotny · 2024
Closest in time.