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Video diffusion models have recently made great progress in generation quality, but are still limited by the high memory and computational requirements.
UCF101: A dataset of 101 human actions classes from videos in the wild
Khurram Soomro, Amir Roshan Zamir, and Mubarak Shah · 2012
Earlier work this paper cites.
Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2015
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Unsupervised learning of video representations using LSTMs
Nitish Srivastava, Elman Mansimov, and Ruslan Salakhudinov · 2015
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Unsupervised learning for physical interaction through video prediction
Chelsea Finn, Ian Goodfellow, and Sergey Levine · 2016
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Msr-vtt: A large video description dataset for bridging video and language
Jun Xu, Tao Mei, Ting Yao, and Yong Rui · 2016
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Quo vadis, action recognition? a new model and the kinetics dataset
Joao Carreira and Andrew Zisserman · 2017
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Unsupervised learning of disentangled representations from video
Emily Denton and Vighnesh Birodkar · 2017
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Arbitrary style transfer in real-time with adaptive instance normalization
Xun Huang and Serge Belongie · 2017
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Video pixel networks
Nal Kalchbrenner, Aäron Oord, Karen Simonyan, Ivo Danihelka, Oriol Vinyals, Alex Graves, and Koray Kavukcuoglu · 2017
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Neural discrete representation learning
Aaron van den Oord, Oriol Vinyals, and Koray Kavukcuoglu · 2017
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Decomposing motion and content for natural video sequence prediction
Ruben Villegas, Jimei Yang, Seunghoon Hong, Xunyu Lin, and Honglak Lee · 2017
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Stochastic variational video prediction
Mohammad Babaeizadeh, Chelsea Finn, Dumitru Erhan, Roy H Campbell, and Sergey Levine · 2018
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Stochastic video generation with a learned prior
Emily Denton and Rob Fergus · 2018
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Deepfake video detection using recurrent neural networks
David Guera and Edward J. Delp · 2018
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Learning to decompose and disentangle representations for video prediction
Jun-Ting Hsieh, Bingbin Liu, De-An Huang, Li Fei-Fei, and Juan Carlos Niebles · 2018
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Stochastic adversarial video prediction
Alex X Lee, Richard Zhang, Frederik Ebert, Pieter Abbeel, Chelsea Finn, and Sergey Levine · 2018
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MoCoGAN: Decomposing motion and content for video generation
Sergey Tulyakov, Ming-Yu Liu, Xiaodong Yang, and Jan Kautz · 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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Howto100m: Learning a text-video embedding by watching hundred million narrated video clips
Antoine Miech, Dimitri Zhukov, Jean-Baptiste Alayrac, Makarand Tapaswi, Ivan Laptev, and Josef Sivic · 2019
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High fidelity video prediction with large stochastic recurrent neural networks
Ruben Villegas, Arkanath Pathak, Harini Kannan, Dumitru Erhan, Quoc V Le, and Honglak Lee · 2019
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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, et al · 2020
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Stochastic latent residual video prediction
Jean-Yves Franceschi, Edouard Delasalles, Mickaël Chen, Sylvain Lamprier, and Patrick Gallinari · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Analyzing and improving the image quality of StyleGAN
Tero Karras, Samuli Laine, Miika Aittala, Janne Hellsten, Jaakko Lehtinen, and Timo Aila · 2020
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Videoflow: A conditional flow-based model for stochastic video generation
Manoj Kumar, Mohammad Babaeizadeh, Dumitru Erhan, Chelsea Finn, Sergey Levine, Laurent Dinh, and Durk Kingma · 2020
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Transformation-based adversarial video prediction on large-scale data
Pauline Luc, Aidan Clark, Sander Dieleman, Diego de Las Casas, Yotam Doron, Albin Cassirer, and Karen Simonyan · 2020
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Ruslan Rakhimov, Denis Volkhonskiy, Alexey Artemov, Denis Zorin, and Evgeny Burnaev · 2020
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Scaling autoregressive video models
Dirk Weissenborn, Oscar Täckström, and Jakob Uszkoreit · 2020
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Vivit: A video vision transformer
Anurag Arnab, Mostafa Dehghani, Georg Heigold, Chen Sun, Mario Lučić, and Cordelia Schmid · 2021
Cited alongside, same era.
Frozen in time: A joint video and image encoder for end-to-end retrieval
Max Bain, Arsha Nagrani, Gül Varol, and Andrew Zisserman · 2021
Cited alongside, same era.
Is space-time attention all you need for video understanding?
Gedas Bertasius, Heng Wang, and Lorenzo Torresani · 2021
Cited alongside, same era.
Taming transformers for high-resolution image synthesis
Patrick Esser, Robin Rombach, and Björn Ommer · 2021
Cited alongside, same era.
StyleVideoGAN: A temporal generative model using a pretrained StyleGAN
Gereon Fox, Ayush Tewari, Mohamed Elgharib, and Christian Theobalt · 2021
Nüwa: Visual synthesis pre-training for neural visual world creation
Chenfei Wu, Jian Liang, Lei Ji, Fan Yang, Yuejian Fang, Daxin Jiang, and Nan Duan · 2022
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Diffusion probabilistic modeling for video generation
Ruihan Yang, Prakhar Srivastava, and Stephan Mandt · 2022
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Generating videos with dynamics-aware implicit generative adversarial networks
Sihyun Yu, Jihoon Tack, Sangwoo Mo, Hyunsu Kim, Junho Kim, Jung-Woo Ha, and Jinwoo Shin · 2022
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LION: Latent point diffusion models for 3d shape generation
Xiaohui Zeng, Arash Vahdat, Francis Williams, Zan Gojcic, Or Litany, Sanja Fidler, and Karsten Kreis · 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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Cited alongside, same era.
Latent neural differential equations for video generation
Cade Gordon and Natalie Parde · 2021
Cited alongside, same era.
Revisiting hierarchical approach for persistent long-term video prediction
Wonkwang Lee, Whie Jung, Han Zhang, Ting Chen, Jing Yu Koh, Thomas Huang, Hyungsuk Yoon, Honglak Lee, and Seunghoon Hong · 2021
Cited alongside, same era.
Temporal shift GAN for large scale video generation
Andres Munoz, Mohammadreza Zolfaghari, Max Argus, and Thomas Brox · 2021
Cited alongside, same era.
Improved denoising diffusion probabilistic models
Alexander Quinn Nichol and Prafulla Dhariwal · 2021
Cited alongside, same era.
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, Gretchen Krueger, and Ilya Sutskever · 2021
Cited alongside, same era.
A good image generator is what you need for high-resolution video synthesis
Yu Tian, Jian Ren, Menglei Chai, Kyle Olszewski, Xi Peng, Dimitris N Metaxas, and Sergey Tulyakov · 2021
Cited alongside, same era.
Latent-shift: Latent diffusion with temporal shift for efficient text-to-video generation
Jie An, Songyang Zhang, Harry Yang, Sonal Gupta, Jia-Bin Huang, Jiebo Luo, and Xi Yin · 2023
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LDM3D: Latent diffusion model for 3d
Gabriela Ben Melech Stan, Diana Wofk, Scottie Fox, Alex Redden, Will Saxton, Jean Yu, Estelle Aflalo, Shao-Yen Tseng, Fabio Nonato, Matthias Muller, et al · 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
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Instructpix2pix: Learning to follow image editing instructions
Tim Brooks, Aleksander Holynski, and Alexei A Efros · 2023
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An image is worth one word: Personalizing text-to-image generation using textual inversion
Rinon Gal, Yuval Alaluf, Yuval Atzmon, Or Patashnik, Amit Haim Bermano, Gal Chechik, and Daniel Cohen-or · 2023
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Preserve your own correlation: A noise prior for video diffusion models
Songwei Ge, Seungjun Nah, Guilin Liu, Tyler Poon, Andrew Tao, Bryan Catanzaro, David Jacobs, Jia-Bin Huang, Ming-Yu Liu, and Yogesh Balaji · 2023
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Animatediff: Animate your personalized text-to-image diffusion models without specific tuning
Yuwei Guo, Ceyuan Yang, Anyi Rao, Yaohui Wang, Yu Qiao, Dahua Lin, and Bo Dai · 2023
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Cogvideo: Large-scale pretraining for text-to-video generation via transformers
Wenyi Hong, Ming Ding, Wendi Zheng, Xinghan Liu, and Jie Tang · 2023
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Text2Performer: Text-driven human video generation
Yuming Jiang, Shuai Yang, Tong Liang Koh, Wayne Wu, Chen Change Loy, and Ziwei Liu · 2023
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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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Collaborative score distillation for consistent visual synthesis
Subin Kim, Kyungmin Lee, June Suk Choi, Jongheon Jeong, Kihyuk Sohn, and Jinwoo Shin · 2023
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Videodirectorgpt: Consistent multi-scene video generation via llm-guided planning
Han Lin, Abhay Zala, Jaemin Cho, and Mohit Bansal · 2023
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Vdt: An empirical study on video diffusion with transformers
Haoyu Lu, Guoxing Yang, Nanyi Fei, Yuqi Huo, Zhiwu Lu, Ping Luo, and Mingyu Ding · 2023
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Videofusion: Decomposed diffusion models for high-quality video generation
Zhengxiong Luo, Dayou Chen, Yingya Zhang, Yan Huang, Liang Wang, Yujun Shen, Deli Zhao, Jingren Zhou, and Tieniu Tan · 2023
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Dreamix: Video diffusion models are general video editors
Eyal Molad, Eliahu Horwitz, Dani Valevski, Alex Rav Acha, Yossi Matias, Yael Pritch, Yaniv Leviathan, and Yedid Hoshen · 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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Scalable diffusion models with transformers
William Peebles and Saining Xie · 2023
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Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation
Nataniel Ruiz, Yuanzhen Li, Varun Jampani, Yael Pritch, Michael Rubinstein, and Kfir Aberman · 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, et al · 2023
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Phenaki: Variable length video generation from open domain textual descriptions
Ruben Villegas, Mohammad Babaeizadeh, Pieter-Jan Kindermans, Hernan Moraldo, Han Zhang, Mohammad Taghi Saffar, Santiago Castro, Julius Kunze, and Dumitru Erhan · 2023
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Geometric latent diffusion models for 3d molecule generation
Minkai Xu, Alexander S Powers, Ron O Dror, Stefano Ermon, and Jure Leskovec · 2023
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Show-1: Marrying pixel and latent diffusion models for text-to-video generation
David Junhao Zhang, Jay Zhangjie Wu, Jia-Wei Liu, Rui Zhao, Lingmin Ran, Yuchao Gu, Difei Gao, and Mike Zheng Shou · 2023
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