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While text-to-video diffusion models have made significant strides, many still face challenges in generating videos with temporal consistency.
Tweedie’s formula and selection bias
Bradley Efron · 2011
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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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Flow-grounded spatial-temporal video prediction from still images
Yijun Li, Chen Fang, Jimei Yang, Zhaowen Wang, Xin Lu, and Ming-Hsuan Yang · 2018
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Video generation from single semantic label map
Junting Pan, Chengyu Wang, Xu Jia, Jing Shao, Lu Sheng, Junjie Yan, and Xiaogang Wang · 2019
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Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2020
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Raft: Recurrent all-pairs field transforms for optical flow
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Frozen in time: A joint video and image encoder for end-to-end retrieval
Max Bain, Arsha Nagrani, Gül Varol, and Andrew Zisserman · 2021
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Diffusion models beat GANs on image synthesis
Prafulla Dhariwal and Alexander Quinn 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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Classifier-free diffusion guidance
Jonathan Ho and Tim Salimans · 2021
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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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Diffusionclip: Text-guided diffusion models for robust image manipulation
Gwanghyun Kim, Taesung Kwon, and Jong Chul Ye · 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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Chain of thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, brian ichter, Fei Xia, Ed H. Chi, Quoc V Le, and Denny Zhou · 2022
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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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Videocrafter1: Open diffusion models for high-quality video generation, 2023
Haoxin Chen, Menghan Xia, Yingqing He, Yong Zhang, Xiaodong Cun, Shaoshu Yang, Jinbo Xing, Yaofang Liu, Qifeng Chen, Xintao Wang, Chao Weng, and Ying Shan · 2023
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Diffusion posterior sampling for general noisy inverse problems
Hyungjin Chung, Jeongsol Kim, Michael Thompson Mccann, Marc Louis Klasky, and Jong Chul Ye · 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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Motion guidance: Diffusion-based image editing with differentiable motion estimators
Daniel Geng and Andrew Owens · 2024
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Animatediff: Animate your personalized text-to-image diffusion models without specific tuning
Yuwei Guo, Ceyuan Yang, Anyi Rao, Zhengyang Liang, Yaohui Wang, Yu Qiao, Maneesh Agrawala, Dahua Lin, and Bo Dai · 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, Yaohui Wang, Xinyuan Chen, Limin Wang, Dahua Lin, Yu Qiao, and Ziwei Liu · 2024
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Dreamsampler: Unifying diffusion sampling and score distillation for image manipulation
Jeongsol Kim, Geon Yeong Park, and Jong Chul Ye · 2024
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Videoguide: Improving video diffusion models without training through a teacher’s guide, 2024
Dohun Lee, Bryan S Kim, Geon Yeong Park, and Jong Chul Ye · 2024
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Conditional image-to-video generation with latent flow diffusion models
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Hard prompts made easy: Gradient-based discrete optimization for prompt tuning and discovery
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