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Video diffusion models have shown great potential in generating high-quality videos, making them an increasingly popular focus.
Generative adversarial networks
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 · 2014
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Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network
Wenzhe Shi, Jose Caballero, Ferenc Huszár, Johannes Totz, Andrew P Aitken, Rob Bishop, Daniel Rueckert, and Zehan Wang · 2016
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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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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Score-based generative modeling through stochastic differential equations
Yang Song, Jascha Sohl-Dickstein, Diederik P Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole · 2020
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Classifier-free diffusion guidance
Jonathan Ho and Tim Salimans · 2021
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Lora: Low-rank adaptation of large language models
Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen · 2021
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Latent video diffusion models for high-fidelity video generation with arbitrary lengths
Yingqing He, Tianyu Yang, Yong Zhang, Ying Shan, and Qifeng Chen · 2022
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Jonathan Ho, Tim Salimans, Alexey Gritsenko, William Chan, Mohammad Norouzi, and David J Fleet · 2022
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Progressive distillation for fast sampling of diffusion models
Tim Salimans and Jonathan Ho · 2022
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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 · 2022
Cited alongside, same era.
Consistency trajectory models: Learning probability flow ode trajectory of diffusion
Dongjun Kim, Chieh-Hsin Lai, Wei-Hsiang Liao, Naoki Murata, Yuhta Takida, Toshimitsu Uesaka, Yutong He, Yuki Mitsufuji, and Stefano Ermon · 2023
Cited alongside, same era.
Videogen: A reference-guided latent diffusion approach for high definition text-to-video generation
Xin Li, Wenqing Chu, Ye Wu, Weihang Yuan, Fanglong Liu, Qi Zhang, Fu Li, Haocheng Feng, Errui Ding, and Jingdong Wang · 2023
Cited alongside, same era.
Latent consistency models: Synthesizing high-resolution images with few-step inference
Simian Luo, Yiqin Tan, Longbo Huang, Jian Li, and Hang Zhao · 2023
Cited alongside, same era.
Sdxl-lightning: Progressive adversarial diffusion distillation
Shanchuan Lin, Anran Wang, and Xiao Yang · 2024
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Openvid-1m: A large-scale high-quality dataset for text-to-video generation
Kepan Nan, Rui Xie, Penghao Zhou, Tiehan Fan, Zhenheng Yang, Zhijie Chen, Xiang Li, Jian Yang, and Ying Tai · 2024
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Hyper-sd: Trajectory segmented consistency model for efficient image synthesis
Yuxi Ren, Xin Xia, Yanzuo Lu, Jiacheng Zhang, Jie Wu, Pan Xie, Xing Wang, and Xuefeng Xiao · 2024
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Fast high-resolution image synthesis with latent adversarial diffusion distillation
Axel Sauer, Frederic Boesel, Tim Dockhorn, Andreas Blattmann, Patrick Esser, and Robin Rombach · 2024
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On distillation of guided diffusion models
Chenlin Meng, Robin Rombach, Ruiqi Gao, Diederik Kingma, Stefano Ermon, Jonathan Ho, and Tim Salimans · 2023
Cited alongside, same era.
Dinov2: Learning robust visual features without supervision
Maxime Oquab, Timothée Darcet, Théo Moutakanni, Huy Vo, Marc Szafraniec, Vasil Khalidov, Pierre Fernandez, Daniel Haziza, Francisco Massa, Alaaeldin El-Nouby, et al · 2023
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Improved techniques for training consistency models
Yang Song and Prafulla Dhariwal · 2023
Cited alongside, same era.
Yang Song, Prafulla Dhariwal, Mark Chen, and Ilya Sutskever · 2023
Cited alongside, same era.
Videolcm: Video latent consistency model
Xiang Wang, Shiwei Zhang, Han Zhang, Yu Liu, Yingya Zhang, Changxin Gao, and Nong Sang · 2023
Cited alongside, same era.
Jonathan Heek, Emiel Hoogeboom, and Tim Salimans · 2024
Cited alongside, same era.
T2v-turbo: Breaking the quality bottleneck of video consistency model with mixed reward feedback
Jiachen Li, Weixi Feng, Tsu-Jui Fu, Xinyi Wang, Sugato Basu, Wenhu Chen, and William Yang Wang · 2024
Cited alongside, same era.
Stable video diffusion: Scaling latent video diffusion models to large datasets
Andreas Blattmann, Tim Dockhorn, Sumith Kulal, Daniel Mendelevitch, Maciej Kilian, Dominik Lorenz, Yam Levi, Zion English, Vikram Voleti, Adam Letts, et al
Cited in the paper.
Xiaoyu Shi, Zhaoyang Huang, Fu-Yun Wang, Weikang Bian, Dasong Li, Yi Zhang, Manyuan Zhang, Ka Chun Cheung, Simon See, Hongwei Qin, et al · 2024
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Ufogen: You forward once large scale text-to-image generation via diffusion gans
Yanwu Xu, Yang Zhao, Zhisheng Xiao, and Tingbo Hou · 2024
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Perflow: Piecewise rectified flow as universal plug-and-play accelerator
Hanshu Yan, Xingchao Liu, Jiachun Pan, Jun Hao Liew, Qiang Liu, and Jiashi Feng · 2024
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Sf-v: Single forward video generation model
Zhixing Zhang, Yanyu Li, Yushu Wu, Yanwu Xu, Anil Kag, Ivan Skorokhodov, Willi Menapace, Aliaksandr Siarohin, Junli Cao, Dimitris Metaxas, et al · 2024
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Trajectory consistency distillation
Jianbin Zheng, Minghui Hu, Zhongyi Fan, Chaoyue Wang, Changxing Ding, Dacheng Tao, and Tat-Jen Cham · 2024
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Mingyuan Zhou, Huangjie Zheng, Zhendong Wang, Mingzhang Yin, and Hai Huang · 2024
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