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Generating videos with realistic and physically plausible motion is one of the main recent challenges in computer vision.
Flocks, herds and schools: A distributed behavioral model
Craig W Reynolds · 1987
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Image quality assessment: from error visibility to structural similarity
Zhou Wang, Alan C Bovik, Hamid R Sheikh, and Eero P Simoncelli · 2004
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Open source computer vision library
Itseez · 2015
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U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 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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Neural discrete representation learning
Aaron Van Den Oord, Oriol Vinyals, et al · 2017
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Generative modeling by estimating gradients of the data distribution
Yang Song and Stefano Ermon · 2019
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A review of video generation approaches
Rishika Bhagwatkar, Saketh Bachu, Khurshed Fitter, Akshay Kulkarni, and Shital Chiddarwar · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Learning to control pdes with differentiable physics
Philipp Holl, Nils Thuerey, and Vladlen Koltun · 2020
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Raft: Recurrent all-pairs field transforms for optical flow
Zachary Teed and Jia Deng · 2020
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Agentpy: A package for agent-based modeling in python
Joël Foramitti · 2021
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Classifier-free diffusion guidance
Jonathan Ho and Tim Salimans · 2021
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Msu video frame interpolation benchmark dataset, 2022
MSU Graphics and Media Lab · 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
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Latentwarp: Consistent diffusion latents for zero-shot video-to-video translation
Yuxiang Bao, Di Qiu, Guoliang Kang, Baochang Zhang, Bo Jin, Kaiye Wang, and Pengfei Yan · 2023
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Align your latents: High-resolution video synthesis with latent diffusion models
Andreas Blattmann, Robin Rombach, Huan Ling, Tim Dockhorn, Seung Wook Kim, Sanja Fidler, and Karsten Kreis · 2023
Text2video-zero: Text-to-image diffusion models are zero-shot video generators
Levon Khachatryan, Andranik Movsisyan, Vahram Tadevosyan, Roberto Henschel, Zhangyang Wang, Shant Navasardyan, and Humphrey Shi · 2023
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Null-text inversion for editing real images using guided diffusion models
Ron Mokady, Amir Hertz, Kfir Aberman, Yael Pritch, and Daniel Cohen-Or · 2023
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Conditional image-to-video generation with latent flow diffusion models
Haomiao Ni, Changhao Shi, Kai Li, Sharon X Huang, and Martin Renqiang Min · 2023
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Sdxl: Improving latent diffusion models for high-resolution image synthesis
Dustin Podell, Zion English, Kyle Lacey, Andreas Blattmann, Tim Dockhorn, Jonas Müller, Joe Penna, and Robin Rombach · 2023
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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, Devi Parikh, Sonal Gupta, and Yaniv Taigman · 2023
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Instructpix2pix: Learning to follow image editing instructions
Tim Brooks, Aleksander Holynski, and Alexei A Efros · 2023
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Generative rendering: Controllable 4d-guided video generation with 2d diffusion models
Shengqu Cai, Duygu Ceylan, Matheus Gadelha, Chun-Hao Paul Huang, Tuanfeng Yang Wang, and Gordon Wetzstein · 2023
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Pix2video: Video editing using image diffusion
Duygu Ceylan, Chun-Hao P Huang, and Niloy J Mitra · 2023
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Diffusion self-guidance for controllable image generation
Dave Epstein, Allan Jabri, Ben Poole, Alexei Efros, and Aleksander Holynski · 2023
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Prompt-to-prompt image editing with cross-attention control
Amir Hertz, Ron Mokady, Jay Tenenbaum, Kfir Aberman, Yael Pritch, and Daniel Cohen-or · 2023
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Imagen video: High definition video generation with diffusion models
Jonathan Ho, William Chan, Chitwan Saharia, Jay Whang, Ruiqi Gao, Alexey Gritsenko, Diederik P Kingma, Ben Poole, Mohammad Norouzi, David J Fleet, et al
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Tune-a-video: One-shot tuning of image diffusion models for text-to-video generation
Jay Zhangjie Wu, Yixiao Ge, Xintao Wang, Stan Weixian Lei, Yuchao Gu, Yufei Shi, Wynne Hsu, Ying Shan, Xiaohu Qie, and Mike Zheng Shou · 2023
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Adding conditional control to text-to-image diffusion models
Lvmin Zhang, Anyi Rao, and Maneesh Agrawala · 2023
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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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Motion guidance: Diffusion-based image editing with differentiable motion estimators
Daniel Geng and Andrew Owens · 2024
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Tokenflow: Consistent diffusion features for consistent video editing
Michal Geyer, Omer Bar-Tal, Shai Bagon, and Tali Dekel · 2024
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