Fetching the paper…
Reading the bibliography…
Diffusion models have emerged as the de facto paradigm for video generation.
Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2010
Earlier work this paper cites.
Score-based generative modeling through stochastic differential equations
Yang Song, Jascha Sohl-Dickstein, Diederik P Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole · 2011
Earlier work this paper cites.
U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
Earlier work this paper cites.
Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
Earlier work this paper cites.
3d u-net: learning dense volumetric segmentation from sparse annotation
Özgün Çiçek, Ahmed Abdulkadir, Soeren S Lienkamp, Thomas Brox, and Olaf Ronneberger · 2016
Earlier work this paper cites.
Memory-efficient backpropagation through time
Audrunas Gruslys, Rémi Munos, Ivo Danihelka, Marc Lanctot, and Alex Graves · 2016
Earlier work this paper cites.
Temporal segment networks: Towards good practices for deep action recognition
Limin Wang, Yuanjun Xiong, Zhe Wang, Yu Qiao, Dahua Lin, Xiaoou Tang, and Luc Van Gool · 2016
Earlier work this paper cites.
Overcoming catastrophic forgetting in neural networks
James Kirkpatrick, Razvan Pascanu, Neil Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei A Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, et al · 2017
Earlier work this paper cites.
Sync-draw: Automatic video generation using deep recurrent attentive architectures
Gaurav Mittal, Tanya Marwah, and Vineeth N Balasubramanian · 2017
Earlier work this paper cites.
To create what you tell: Generating videos from captions
Yingwei Pan, Zhaofan Qiu, Ting Yao, Houqiang Li, and Tao Mei · 2017
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.
Video generation from text
Yitong Li, Martin Min, Dinghan Shen, David Carlson, and Lawrence Carin · 2018
Earlier work this paper cites.
Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
Earlier work this paper cites.
Offline reinforcement learning: Tutorial, review, and perspectives on open problems
Sergey Levine, Aviral Kumar, George Tucker, and Justin Fu · 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.
A general language assistant as a laboratory for alignment
Amanda Askell, Yuntao Bai, Anna Chen, Dawn Drain, Deep Ganguli, Tom Henighan, Andy Jones, Nicholas Joseph, Ben Mann, Nova DasSarma, et al · 2021
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.
Taming transformers for high-resolution image synthesis
Patrick Esser, Robin Rombach, and Björn Ommer · 2021
Earlier work this paper cites.
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
Earlier work this paper cites.
Diffwave: A versatile diffusion model for audio synthesis
Zhifeng Kong, Wei Ping, Jiaji Huang, Kexin Zhao, and Bryan Catanzaro · 2021
Earlier work this paper cites.
Sdedit: Guided image synthesis and editing with stochastic differential equations
Chenlin Meng, Yutong He, Yang Song, Jiaming Song, Jiajun Wu, Jun-Yan Zhu, and Stefano Ermon · 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.
Laion-400m: Open dataset of clip-filtered 400 million image-text pairs
Christoph Schuhmann, Richard Vencu, Romain Beaumont, Robert Kaczmarczyk, Clayton Mullis, Aarush Katta, Theo Coombes, Jenia Jitsev, and Aran Komatsuzaki · 2021
Earlier work this paper cites.
Godiva: Generating open-domain videos from natural descriptions
Chenfei Wu, Lun Huang, Qianxi Zhang, Binyang Li, Lei Ji, Fan Yang, Guillermo Sapiro, and Nan Duan · 2021
Earlier work this paper cites.
Videogpt: Video generation using vq-vae and transformers
Wilson Yan, Yunzhi Zhang, Pieter Abbeel, and Aravind Srinivas · 2021
Cited alongside, same era.
Diffedit: Diffusion-based semantic image editing with mask guidance
Guillaume Couairon, Jakob Verbeek, Holger Schwenk, and Matthieu Cord · 2022
Cited alongside, same era.
Latent video diffusion models for high-fidelity long video generation
Yingqing He, Tianyu Yang, Yong Zhang, Ying Shan, and Qifeng Chen · 2022
Cited alongside, same era.
Classifier-free diffusion guidance
Jonathan Ho and Tim Salimans · 2022
Cited alongside, same era.
Cogvideo: Large-scale pretraining for text-to-video generation via transformers
Tell me what happened: Unifying text-guided video completion via multimodal masked video generation
Tsu-Jui Fu, Licheng Yu, Ning Zhang, Cheng-Yang Fu, Jong-Chyi Su, William Yang Wang, and Sean Bell · 2023
Closest in time.
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
Closest in time.
Tokenflow: Consistent diffusion features for consistent video editing
Michal Geyer, Omer Bar-Tal, Shai Bagon, and Tali Dekel · 2023
Closest in time.
Reuse and diffuse: Iterative denoising for text-to-video generation
Jiaxi Gu, Shicong Wang, Haoyu Zhao, Tianyi Lu, Xing Zhang, Zuxuan Wu, Songcen Xu, Wei Zhang, Yu-Gang Jiang, and Hang Xu · 2023
Closest in time.
Animate-a-story: Storytelling with retrieval-augmented video generation
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Wenyi Hong, Ming Ding, Wendi Zheng, Xinghan Liu, and Jie Tang · 2022
Cited alongside, same era.
Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation
Junnan Li, Dongxu Li, Caiming Xiong, and Steven Hoi · 2022
Cited alongside, same era.
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
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.
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.
Stylegan-v: A continuous video generator with the price, image quality and perks of stylegan2
Ivan Skorokhodov, Sergey Tulyakov, and Mohamed Elhoseiny · 2022
Cited alongside, same era.
Phenaki: Variable length video generation from open domain textual description
Ruben Villegas, Mohammad Babaeizadeh, Pieter-Jan Kindermans, Hernan Moraldo, Han Zhang, Mohammad Taghi Saffar, Santiago Castro, Julius Kunze, and Dumitru Erhan · 2022
Cited alongside, same era.
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
Cited alongside, same era.
Yingqing He, Menghan Xia, Haoxin Chen, Xiaodong Cun, Yuan Gong, Jinbo Xing, Yong Zhang, Xintao Wang, Chao Weng, Ying Shan, et al · 2023
Closest in time.
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
Closest in time.
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 · 2023
Closest in time.
Gd-vdm: Generated depth for better diffusion-based video generation
Ariel Lapid, Idan Achituve, Lior Bracha, and Ethan Fetaya · 2023
Closest in time.
Aligning text-to-image models using human feedback
Kimin Lee, Hao Liu, Moonkyung Ryu, Olivia Watkins, Yuqing Du, Craig Boutilier, Pieter Abbeel, Mohammad Ghavamzadeh, and Shixiang Shane Gu · 2023
Closest in time.
Agiqa-3k: An open database for ai-generated image quality assessment
Chunyi Li, Zicheng Zhang, Haoning Wu, Wei Sun, Xiongkuo Min, Xiaohong Liu, Guangtao Zhai, and Weisi Lin · 2023
Closest in time.
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
Closest in time.
GPT-4 technical report, 2023
OpenAI · 2023
Closest in time.
Aligning text-to-image diffusion models with reward backpropagation
Mihir Prabhudesai, Anirudh Goyal, Deepak Pathak, and Katerina Fragkiadaki · 2023
Closest in time.
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
Closest in time.
Hierarchical spatio-temporal decoupling for text-to-video generation
Zhiwu Qing, Shiwei Zhang, Jiayu Wang, Xiang Wang, Yujie Wei, Yingya Zhang, Changxin Gao, and Nong Sang · 2023
Closest in time.
Mm-diffusion: Learning multi-modal diffusion models for joint audio and video generation
Ludan Ruan, Yiyang Ma, Huan Yang, Huiguo He, Bei Liu, Jianlong Fu, Nicholas Jing Yuan, Qin Jin, and Baining Guo · 2023
Closest in time.
Any-to-any generation via composable diffusion
Zineng Tang, Ziyi Yang, Chenguang Zhu, Michael Zeng, and Mohit Bansal · 2023
Closest in time.
Llama: Open and efficient foundation language models, 2023
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, Aurelien Rodriguez, Armand Joulin, Edouard Grave, and Guillaume Lample · 2023
Closest in time.
Fabric: Personalizing diffusion models with iterative feedback
Dimitri von Rütte, Elisabetta Fedele, Jonathan Thomm, and Lukas Wolf · 2023
Closest in time.
Dreamvideo: Composing your dream videos with customized subject and motion
Yujie Wei, Shiwei Zhang, Zhiwu Qing, Hangjie Yuan, Zhiheng Liu, Yu Liu, Yingya Zhang, Jingren Zhou, and Hongming Shan · 2023
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 · 2023
Closest in time.
Dragnuwa: Fine-grained control in video generation by integrating text, image, and trajectory
Shengming Yin, Chenfei Wu, Jian Liang, Jie Shi, Houqiang Li, Gong Ming, and Nan Duan · 2023
Closest in time.
Video probabilistic diffusion models in projected latent space
Sihyun Yu, Kihyuk Sohn, Subin Kim, and Jinwoo Shin · 2023
Closest in time.
Junchen Zhu, Huan Yang, Huiguo He, Wenjing Wang, Zixi Tuo, Wen-Huang Cheng, Lianli Gao, Jingkuan Song, and Jianlong Fu · 2023
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.