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While recent foundational video generators produce visually rich output, they still struggle with appearance drift, where objects gradually degrade or change inconsistently across frames, breaking visual coherence.
Robust estimation of a location parameter
Peter J Huber · 1992
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Particle video: Long-range motion estimation using point trajectories
Peter Sand and Seth Teller · 2008
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A connection between score matching and denoising autoencoders
Pascal Vincent · 2011
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Auto-encoding variational bayes
Diederik P Kingma · 2013
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Video segmentation by tracking many figure-ground segments
Fuxin Li, Taeyoung Kim, Ahmad Humayun, David Tsai, and James M Rehg · 2013
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Jumpcut: non-successive mask transfer and interpolation for video cutout
Qingnan Fan, Fan Zhong, Dani Lischinski, Daniel Cohen-Or, and Baoquan Chen · 2015
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Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
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Pre-constancy vision in infants
Jiale Yang, So Kanazawa, Masami K Yamaguchi, and Isamu Motoyoshi · 2015
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A benchmark dataset and evaluation methodology for video object segmentation
Federico Perazzi, Jordi Pont-Tuset, Brian McWilliams, Luc Van Gool, Markus Gross, and Alexander Sorkine-Hornung · 2016
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
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Fixing weight decay regularization in adam
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The 2017 davis challenge on video object segmentation
Jordi Pont-Tuset, Federico Perazzi, Sergi Caelles, Pablo Arbeláez, Alex Sorkine-Hornung, and Luc Van Gool · 2017
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The 2018 davis challenge on video object segmentation
Sergi Caelles, Alberto Montes, Kevis-Kokitsi Maninis, Yuhua Chen, Luc Van Gool, Federico Perazzi, and Jordi Pont-Tuset · 2018
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Towards accurate generative models of video: A new metric & challenges
Thomas Unterthiner, Sjoerd Van Steenkiste, Karol Kurach, Raphael Marinier, Marcin Michalski, and Sylvain Gelly · 2018
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The unreasonable effectiveness of deep features as a perceptual metric
Richard Zhang, Phillip Isola, Alexei A Efros, Eli Shechtman, and Oliver Wang · 2018
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Creatures great and smal: Recovering the shape and motion of animals from video
Benjamin Biggs, Thomas Roddick, Andrew Fitzgibbon, and Roberto Cipolla · 2019
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Space-time correspondence as a contrastive random walk
Allan Jabri, Andrew Owens, and Alexei Efros · 2020
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Raft: Recurrent all-pairs field transforms for optical flow
Zachary Teed and Jia Deng · 2020
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Deep vit features as dense visual descriptors
Shir Amir, Yossi Gandelsman, Shai Bagon, and Tali Dekel · 2021
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Emerging properties in self-supervised vision transformers
Mathilde Caron, Hugo Touvron, Ishan Misra, Hervé Jégou, Julien Mairal, Piotr Bojanowski, and Armand Joulin · 2021
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Diffusion models beat gans on image synthesis
Prafulla Dhariwal and Alexander Nichol · 2021
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An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, and Neil Houlsby · 2021
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Musiq: Multi-scale image quality transformer
Junjie Ke, Qifei Wang, Yilin Wang, Peyman Milanfar, and Feng Yang · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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High-resolution image synthesis with latent diffusion models
Robin Rombach, A. Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2021
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Tap-vid: A benchmark for tracking any point in a video
Carl Doersch, Ankush Gupta, Larisa Markeeva, Adria Recasens, Lucas Smaira, Yusuf Aytar, Joao Carreira, Andrew Zisserman, and Yi Yang · 2022
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Kubric: A scalable dataset generator
Klaus Greff, Francois Belletti, Lucas Beyer, Carl Doersch, Yilun Du, Daniel Duckworth, David J Fleet, Dan Gnanapragasam, Florian Golemo, Charles Herrmann, et al · 2022
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Particle video revisited: Tracking through occlusions using point trajectories
Adam W Harley, Zhaoyuan Fang, and Katerina Fragkiadaki · 2022
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Latent video diffusion models for high-fidelity long video generation
Yingqing He, Tianyu Yang, Yong Zhang, Ying Shan, and Qifeng Chen · 2022
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Can visual foundation models achieve long-term point tracking?
Görkay Aydemir, Weidi Xie, and Fatma Güney · 2024
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Video generation models as world simulators
Tim Brooks, Bill Peebles, Connor Holmes, Will DePue, Yufei Guo, Li Jing, David Schnurr, Joe Taylor, Troy Luhman, Eric Luhman, Clarence Ng, Ricky Wang, and Aditya Ramesh · 2024
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Deconstructing denoising diffusion models for self-supervised learning. arxiv 2024
X Chen, Z Liu, S Xie, and K He · 2024
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Local all-pair correspondence for point tracking
Seokju Cho, Jiahui Huang, Jisu Nam, Honggyu An, Seungryong Kim, and Joon-Young Lee · 2024
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Elucidating the design space of diffusion-based generative models
Tero Karras, Miika Aittala, Timo Aila, and Samuli Laine · 2022
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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
Cited alongside, same era.
Progressive distillation for fast sampling of diffusion models
Tim Salimans and Jonathan Ho · 2022
Cited alongside, same era.
Make-a-video: Text-to-video generation without text-video data
Uriel Singer, Adam Polyak, Thomas Hayes, Xi Yin, Jie An, Songyang Zhang, Qiyuan Hu, Harry Yang, Oron Ashual, Oran Gafni, et al · 2022
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Magicvideo: Efficient video generation with latent diffusion models
Daquan Zhou, Weimin Wang, Hanshu Yan, Weiwei Lv, Yizhe Zhu, and Jiashi Feng · 2022
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Context-tap: Tracking any point demands spatial context features
Weikang Bian, Zhaoyang Huang, Xiaoyu Shi, Yitong Dong, Yijin Li, and Hongsheng Li · 2023
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Videocrafter1: Open diffusion models for high-quality video generation
Haoxin Chen, Menghan Xia, Yingqing He, Yong Zhang, Xiaodong Cun, Shaoshu Yang, Jinbo Xing, Yaofang Liu, Qifeng Chen, Xintao Wang, et al · 2023
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Carl Doersch, Yi Yang, Dilara Gokay, Pauline Luc, Skanda Koppula, Ankush Gupta, Joseph Heyward, Ross Goroshin, João Carreira, and Andrew Zisserman · 2024
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Diffusion 3d features (diff3f): Decorating untextured shapes with distilled semantic features
Niladri Shekhar Dutt, Sanjeev Muralikrishnan, and Niloy J. Mitra · 2024
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Featup: A model-agnostic framework for features at any resolution
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Videoswap: Customized video subject swapping with interactive semantic point correspondence
Yuchao Gu, Yipin Zhou, Bichen Wu, Licheng Yu, Jia-Wei Liu, Rui Zhao, Jay Zhangjie Wu, David Junhao Zhang, Mike Zheng Shou, and Kevin Tang · 2024
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Vbench: Comprehensive benchmark suite for video generative models
Ziqi Huang, Yinan He, Jiashuo Yu, Fan Zhang, Chenyang Si, Yuming Jiang, Yuanhan Zhang, Tianxing Wu, Qingyang Jin, Nattapol Chanpaisit, et al · 2024
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Cotracker3: Simpler and better point tracking by pseudo-labelling real videos
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Harivo: Harnessing text-to-image models for video generation
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Taptr: Tracking any point with transformers as detection
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Diffusion hyperfeatures: Searching through time and space for semantic correspondence
Grace Luo, Lisa Dunlap, Dong Huk Park, Aleksander Holynski, and Trevor Darrell · 2024
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Movie gen: A cast of media foundation models
Adam Polyak, Amit Zohar, Andrew Brown, Andros Tjandra, Animesh Sinha, Ann Lee, Apoorv Vyas, Bowen Shi, Chih-Yao Ma, Ching-Yao Chuang, et al · 2024
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When does perceptual alignment benefit vision representations?
Shobhita Sundaram, Stephanie Fu, Lukas Muttenthaler, Netanel Y. Tamir, Lucy Chai, Simon Kornblith, Trevor Darrell, and Phillip Isola · 2024
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Lift: A surprisingly simple lightweight feature transform for dense vit descriptors
Saksham Suri, Matthew Walmer, Kamal Gupta, and Abhinav Shrivastava · 2024
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Dino-tracker: Taming dino for self-supervised point tracking in a single video
Narek Tumanyan, Assaf Singer, Shai Bagon, and Tali Dekel · 2024
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Zero-shot video semantic segmentation based on pre-trained diffusion models, 2024
Qian Wang, Abdelrahman Eldesokey, Mohit Mendiratta, Fangneng Zhan, Adam Kortylewski, Christian Theobalt, and Peter Wonka · 2024
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Towards a better metric for text-to-video generation
Jay Zhangjie Wu, Guian Fang, Haoning Wu, Xintao Wang, Yixiao Ge, Xiaodong Cun, David Junhao Zhang, Jia-Wei Liu, Yuchao Gu, Rui Zhao, et al · 2024
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Spatialtracker: Tracking any 2d pixels in 3d space
Yuxi Xiao, Qianqian Wang, Shangzhan Zhang, Nan Xue, Sida Peng, Yujun Shen, and Xiaowei Zhou · 2024
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Representation alignment for generation: Training diffusion transformers is easier than you think
Sihyun Yu, Sangkyung Kwak, Huiwon Jang, Jongheon Jeong, Jonathan Huang, Jinwoo Shin, and Saining Xie · 2024
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Improving 2D Feature Representations by 3D-Aware Fine-Tuning
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A tale of two features: Stable diffusion complements dino for zero-shot semantic correspondence
Junyi Zhang, Charles Herrmann, Junhwa Hur, Luisa Polania Cabrera, Varun Jampani, Deqing Sun, and Ming-Hsuan Yang · 2024
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On unifying video generation and camera pose estimation, 2025
Chun-Hao Paul Huang, Jae Shin Yoon, Hyeonho Jeong, Niloy J. Mitra, and Duygu Ceylan · 2025
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