Fetching the paper…
Reading the bibliography…
In this paper, we focus on enhancing a diffusion-based text-to-video (T2V) model during the post-training phase by distilling a highly capable consistency model from a pretrained T2V model.
Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
Earlier work this paper cites.
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.
Scalable agent alignment via reward modeling: a research direction
Jan Leike, David Krueger, Tom Everitt, Miljan Martic, Vishal Maini, and Shane Legg · 2018
Earlier work this paper cites.
Fine-tuning language models from human preferences
Daniel M Ziegler, Nisan Stiennon, Jeffrey Wu, Tom B Brown, Alec Radford, Dario Amodei, Paul Christiano, and Geoffrey Irving · 2019
Earlier work this paper cites.
Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
Earlier work this paper cites.
Learning to summarize with human feedback
Nisan Stiennon, Long Ouyang, Jeffrey Wu, Daniel Ziegler, Ryan Lowe, Chelsea Voss, Alec Radford, Dario Amodei, and Paul F Christiano · 2020
Earlier work this paper cites.
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.
On the opportunities and risks of foundation models
Rishi Bommasani, Drew A Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, et al · 2021
Earlier work this paper cites.
Emerging properties in self-supervised vision transformers
Mathilde Caron, Hugo Touvron, Ishan Misra, Hervé Jégou, Julien Mairal, Piotr Bojanowski, and Armand Joulin · 2021
Earlier work this paper cites.
Classifier-free diffusion guidance
Jonathan Ho and Tim Salimans · 2021
Earlier work this paper cites.
Lora: Low-rank adaptation of large language models
Edward J Hu, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, Weizhu Chen, et al · 2021
Earlier work this paper cites.
Musiq: Multi-scale image quality transformer
Junjie Ke, Qifei Wang, Yilin Wang, Peyman Milanfar, and Feng Yang · 2021
Earlier work this paper cites.
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, et al · 2021
Earlier work this paper cites.
Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation
Junnan Li, Dongxu Li, Caiming Xiong, and Steven Hoi · 2022
Earlier work this paper cites.
Training language models to follow instructions with human feedback
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al · 2022
Earlier work this paper cites.
Laion-5b: An open large-scale dataset for training next generation image-text models
Christoph Schuhmann, Romain Beaumont, Richard Vencu, Cade Gordon, Ross Wightman, Mehdi Cherti, Theo Coombes, Aarush Katta, Clayton Mullis, Mitchell Wortsman, et al · 2022
Earlier work this paper cites.
Grit: A generative region-to-text transformer for object understanding
Jialian Wu, Jianfeng Wang, Zhengyuan Yang, Zhe Gan, Zicheng Liu, Junsong Yuan, and Lijuan Wang · 2022
Earlier work this paper cites.
Egsde: Unpaired image-to-image translation via energy-guided stochastic differential equations
Min Zhao, Fan Bao, Chongxuan Li, and Jun Zhu · 2022
Earlier work this paper cites.
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
Cited alongside, same era.
Masactrl: Tuning-free mutual self-attention control for consistent image synthesis and editing
Mingdeng Cao, Xintao Wang, Zhongang Qi, Ying Shan, Xiaohu Qie, and Yinqiang Zheng · 2023
Cited alongside, same era.
Videocrafter1: Open diffusion models for high-quality video generation
Haoxin Chen, Menghan Xia, Yingqing He, Yong Zhang, Xiaodong Cun, Shaoshu Yang, Jinbo Xing, Yaofang Liu, Qifeng Chen, Xintao Wang, et al · 2023
Cited alongside, same era.
Directly fine-tuning diffusion models on differentiable rewards
Kevin Clark, Paul Vicol, Kevin Swersky, and David J Fleet · 2023
Cited alongside, same era.
Diffusion self-guidance for controllable image generation
Dave Epstein, Allan Jabri, Ben Poole, Alexei Efros, and Aleksander Holynski · 2023
Cited alongside, same era.
Reinforcement learning for fine-tuning text-to-image diffusion models
Ying Fan, Olivia Watkins, Yuqing Du, Hao Liu, Moonkyung Ryu, Craig Boutilier, Pieter Abbeel, Mohammad Ghavamzadeh, Kangwook Lee, and Kimin Lee · 2024
Closest in time.
Videoscore: Building automatic metrics to simulate fine-grained human feedback for video generation
Xuan He, Dongfu Jiang, Ge Zhang, Max Ku, Achint Soni, Sherman Siu, Haonan Chen, Abhranil Chandra, Ziyan Jiang, Aaran Arulraj, Kai Wang, Quy Duc Do, Yuansheng Ni, Bohan Lyu, Yaswanth Narsupalli, Rongqi Fan, Zhiheng Lyu, Yuchen Lin, and Wenhu Chen · 2024
Closest in time.
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
Closest in time.
Miradata: A large-scale video dataset with long durations and structured captions
Xuan Ju, Yiming Gao, Zhaoyang Zhang, Ziyang Yuan, Xintao Wang, Ailing Zeng, Yu Xiong, Qiang Xu, and Ying Shan · 2024
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Structure and content-guided video synthesis with diffusion models
Patrick Esser, Johnathan Chiu, Parmida Atighehchian, Jonathan Granskog, and Anastasis Germanidis · 2023
Cited alongside, same era.
Training-free structured diffusion guidance for compositional text-to-image synthesis
Weixi Feng, Xuehai He, Tsu-Jui Fu, Varun Jampani, Arjun Reddy Akula, Pradyumna Narayana, Sugato Basu, Xin Eric Wang, and William Yang Wang · 2023
Cited alongside, same era.
Expressive text-to-image generation with rich text
Songwei Ge, Taesung Park, Jun-Yan Zhu, and Jia-Bin Huang · 2023
Cited alongside, same era.
Animatediff: Animate your personalized text-to-image diffusion models without specific tuning, 2023
Yuwei Guo, Ceyuan Yang, Anyi Rao, Zhengyang Liang, Yaohui Wang, Yu Qiao, Maneesh Agrawala, Dahua Lin, and Bo Dai · 2023
Cited alongside, same era.
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
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.
Localizing object-level shape variations with text-to-image diffusion models
Or Patashnik, Daniel Garibi, Idan Azuri, Hadar Averbuch-Elor, and Daniel Cohen-Or · 2023
Cited alongside, same era.
Pick-a-pic: An open dataset of user preferences for text-to-image generation
Yuval Kirstain, Adam Polyak, Uriel Singer, Shahbuland Matiana, Joe Penna, and Omer Levy · 2024
Closest in time.
Open-sora-plan, April 2024
PKU-Yuan Lab and Tuzhan AI etc · 2024
Closest in time.
Motionclone: Training-free motion cloning for controllable video generation
Pengyang Ling, Jiazi Bu, Pan Zhang, Xiaoyi Dong, Yuhang Zang, Tong Wu, Huaian Chen, Jiaqi Wang, and Yi Jin · 2024
Closest in time.
Freecontrol: Training-free spatial control of any text-to-image diffusion model with any condition
Sicheng Mo, Fangzhou Mu, Kuan Heng Lin, Yanli Liu, Bochen Guan, Yin Li, and Bolei Zhou · 2024
Closest in time.
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
Closest in time.
Open-sora: Democratizing efficient video production for all, 2024
Open-Sora · 2024
Closest in time.
Video diffusion alignment via reward gradients
Mihir Prabhudesai, Russell Mendonca, Zheyang Qin, Katerina Fragkiadaki, and Deepak Pathak · 2024
Closest in time.
Direct preference optimization: Your language model is secretly a reward model
Rafael Rafailov, Archit Sharma, Eric Mitchell, Christopher D Manning, Stefano Ermon, and Chelsea Finn · 2024
Closest in time.
T2v-compbench: A comprehensive benchmark for compositional text-to-video generation
Kaiyue Sun, Kaiyi Huang, Xian Liu, Yue Wu, Zihan Xu, Zhenguo Li, and Xihui Liu · 2024
Closest in time.
Vidgen-1m: A large-scale dataset for text-to-video generation
Zhiyu Tan, Xiaomeng Yang, Luozheng Qin, and Hao Li · 2024
Closest in time.
Internvideo2: Scaling video foundation models for multimodal video understanding
Yi Wang, Kunchang Li, Xinhao Li, Jiashuo Yu, Yinan He, Guo Chen, Baoqi Pei, Rongkun Zheng, Jilan Xu, Zun Wang, et al · 2024
Closest in time.
Imagereward: Learning and evaluating human preferences for text-to-image generation
Jiazheng Xu, Xiao Liu, Yuchen Wu, Yuxuan Tong, Qinkai Li, Ming Ding, Jie Tang, and Yuxiao Dong · 2024
Closest in time.
Vript: A video is worth thousands of words
Dongjie Yang, Suyuan Huang, Chengqiang Lu, Xiaodong Han, Haoxin Zhang, Yan Gao, Yao Hu, and Hai Zhao · 2024
Closest in time.
Large-scale reinforcement learning for diffusion models
Yinan Zhang, Eric Tzeng, Yilun Du, and Dmitry Kislyuk · 2024
Closest in time.
Human preference score: Better aligning text-to-image models with human preference
Xiaoshi Wu, Keqiang Sun, Feng Zhu, Rui Zhao, and Hongsheng Li · 2096
Closest in time.