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Text-based diffusion models have exhibited remarkable success in generation and editing, showing great promise for enhancing visual content with their generative prior.
On bayesian adaptive video super resolution
Ce Liu and Deqing Sun · 2013
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 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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Detail-revealing deep video super-resolution
Xin Tao, Hongyun Gao, Renjie Liao, Jue Wang, and Jiaya Jia · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
Earlier work this paper cites.
Deep video super-resolution network using dynamic upsampling filters without explicit motion compensation
Younghyun Jo, Seoung Wug Oh, Jaeyeon Kang, and Seon Joo Kim · 2018
Earlier work this paper cites.
Learning blind video temporal consistency
Wei-Sheng Lai, Jia-Bin Huang, Oliver Wang, Eli Shechtman, Ersin Yumer, and Ming-Hsuan Yang · 2018
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UnFlow: Unsupervised learning of optical flow with a bidirectional census loss
Simon Meister, Junhwa Hur, and Stefan Roth · 2018
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Recovering realistic texture in image super-resolution by deep spatial feature transform
Xintao Wang, Ke Yu, Chao Dong, and Chen Change Loy · 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
Earlier work this paper cites.
NTIRE 2019 challenge on video deblurring and super-resolution: Dataset and study
Seungjun Nah, Sungyong Baik, Seokil Hong, Gyeongsik Moon, Sanghyun Son, Radu Timofte, and Kyoung Mu Lee · 2019
Earlier work this paper cites.
EDVR: Video restoration with enhanced deformable convolutional networks
Xintao Wang, Kelvin CK Chan, Ke Yu, Chao Dong, and Chen Change Loy · 2019
Earlier work this paper cites.
Video enhancement with task-oriented flow
Tianfan Xue, Baian Chen, Jiajun Wu, Donglai Wei, and William T Freeman · 2019
Earlier work this paper cites.
Spatio-temporal filter adaptive network for video deblurring
Shangchen Zhou, Jiawei Zhang, Jinshan Pan, Haozhe Xie, Wangmeng Zuo, and Jimmy Ren · 2019
Earlier work this paper cites.
Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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RAFT: Recurrent all-pairs field transforms for optical flow
Zachary Teed and Jia Deng · 2020
Earlier work this paper cites.
Frozen in Time: A joint video and image encoder for end-to-end retrieval
Max Bain, Arsha Nagrani, Gül Varol, and Andrew Zisserman · 2021
Earlier work this paper cites.
Video super-resolution transformer
Jiezhang Cao, Yawei Li, Kai Zhang, and Luc Van Gool · 2021
Earlier work this paper cites.
BasicVSR: The search for essential components in video super-resolution and beyond
Kelvin CK Chan, Xintao Wang, Ke Yu, Chao Dong, and Chen Change Loy · 2021
Earlier work this paper cites.
ILVR: Conditioning method for denoising diffusion probabilistic models
Jooyoung Choi, Sungwon Kim, Yonghyun Jeong, Youngjune Gwon, and Sungroh Yoon · 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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Deep blind video super-resolution
Jinshan Pan, Haoran Bai, Jiangxin Dong, Jiawei Zhang, and Jinhui Tang · 2021
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Real-ESRGAN: Training real-world blind super-resolution with pure synthetic data
Xintao Wang, Liangbin Xie, Chao Dong, and Ying Shan · 2021
Cited alongside, same era.
Blended diffusion for text-driven editing of natural images
Omri Avrahami, Dani Lischinski, and Ohad Fried · 2022
Cited alongside, same era.
Perception prioritized training of diffusion models
Jooyoung Choi, Jungbeom Lee, Chaehun Shin, Sungwon Kim, Hyunwoo Kim, and Sungroh Yoon · 2022
Cited alongside, same era.
Improving diffusion models for inverse problems using manifold constraints
Hyungjin Chung, Byeongsu Sim, Dohoon Ryu, and Jong Chul Ye · 2022
Cited alongside, same era.
Vector quantized diffusion model for text-to-image synthesis
Shuyang Gu, Dong Chen, Jianmin Bao, Fang Wen, Bo Zhang, Dongdong Chen, Lu Yuan, and Baining Guo · 2022
FLATTEN: optical flow-guided attention for consistent text-to-video editing
Yuren Cong, Mengmeng Xu, Christian Simon, Shoufa Chen, Jiawei Ren, Yanping Xie, Juan-Manuel Perez-Rua, Bodo Rosenhahn, Tao Xiang, and Sen He · 2023
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Structure and content-guided video synthesis with diffusion models
Patrick Esser, Johnathan Chiu, Parmida Atighehchian, Jonathan Granskog, and Anastasis Germanidis · 2023
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Designing an encoder for fast personalization of text-to-image models
Rinon Gal, Moab Arar, Yuval Atzmon, Amit H 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
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Cited alongside, same era.
Prompt-to-prompt image editing with cross attention control
Amir Hertz, Ron Mokady, Jay Tenenbaum, Kfir Aberman, Yael Pritch, and Daniel Cohen-Or · 2022
Cited alongside, same era.
Classifier-free diffusion guidance
Jonathan Ho and Tim Salimans · 2022
Cited alongside, same era.
Denoising diffusion restoration models
Bahjat Kawar, Michael Elad, Stefano Ermon, and Jiaming Song · 2022
Cited alongside, same era.
GLIDE: Towards photorealistic image generation and editing with text-guided diffusion models
Alexander Quinn Nichol, Prafulla Dhariwal, Aditya Ramesh, Pranav Shyam, Pamela Mishkin, Bob Mcgrew, Ilya Sutskever, and Mark Chen · 2022
Cited alongside, same era.
Hierarchical text-conditional image generation with clip latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 2022
Cited alongside, same era.
High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
Cited alongside, same era.
Yuwei Guo, Ceyuan Yang, Anyi Rao, Yaohui Wang, Yu Qiao, Dahua Lin, and Bo Dai · 2023
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LaMD: Latent motion diffusion for video generation
Yaosi Hu, Zhenzhong Chen, and Chong Luo · 2023
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DiffBIR: Towards blind image restoration with generative diffusion prior
Xinqi Lin, Jingwen He, Ziyan Chen, Zhaoyang Lyu, Ben Fei, Bo Dai, Wanli Ouyang, Yu Qiao, and Chao Dong · 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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VIDM: Video implicit diffusion models
Kangfu Mei and Vishal Patel · 2023
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Chong Mou, Xintao Wang, Liangbin Xie, Jian Zhang, Zhongang Qi, Ying Shan, and Xiaohu Qie · 2023
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FateZero: Fusing attentions for zero-shot text-based video editing
Chenyang Qi, Xiaodong Cun, Yong Zhang, Chenyang Lei, Xintao Wang, Ying Shan, and Qifeng Chen · 2023
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Denoising diffusion probabilistic models for robust image super-resolution in the wild
Hshmat Sahak, Daniel Watson, Chitwan Saharia, and David Fleet · 2023
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Pseudoinverse-guided diffusion models for inverse problems
Jiaming Song, Arash Vahdat, Morteza Mardani, and Jan Kautz · 2023
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LLaMA: Open and efficient foundation language models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, et al · 2023
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DiffIR: Efficient diffusion model for image restoration
Bin Xia, Yulun Zhang, Shiyin Wang, Yitong Wang, Xinglong Wu, Yapeng Tian, Wenming Yang, and Luc Van Gool · 2023
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Mitigating artifacts in real-world video super-resolution models
Liangbin Xie, Xintao Wang, Shuwei Shi, Jinjin Gu, Chao Dong, and Ying Shan · 2023
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SimDA: Simple diffusion adapter for efficient video generation
Zhen Xing, Qi Dai, Han Hu, Zuxuan Wu, and Yu-Gang Jiang · 2023
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ResShift: Efficient diffusion model for image super-resolution by residual shifting
Zongsheng Yue, Jianyi Wang, and Chen Change Loy · 2023
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ProPainter: Improving propagation and transformer for video inpainting
Shangchen Zhou, Chongyi Li, Kelvin CK Chan, and Chen Change Loy · 2023
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