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Diffusion models are the de facto approach for generating high-quality images and videos, but learning high-dimensional models remains a formidable task due to computational and optimization challenges.
ImageNet: A Large-scale Hierarchical Image Database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Microsoft COCO: Common Objects in Context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C. Lawrence Zitnick · 2014
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Scheduled sampling for sequence prediction with recurrent neural networks
Samy Bengio, Oriol Vinyals, Navdeep Jaitly, and Noam Shazeer · 2015
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Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks
Emily Denton, Arthur Szlam, and Rob Fergus · 2015
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U-Net : Convolutional Networks for Biomedical Image Segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 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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Conditional Image Generation with PixelCNN Decoders
Aaron van den Oord, Nal Kalchbrenner, Oriol Vinyals, Lasse Espeholt, Alex Graves, and Koray Kavukcuoglu · 2016
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Pixel recurrent neural networks
Aäron Van Den Oord, Nal Kalchbrenner, and Koray Kavukcuoglu · 2016
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
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Video pixel networks
Nal Kalchbrenner, Aäron van den Oord, Karen Simonyan, Ivo Danihelka, Oriol Vinyals, Alex Graves, and Koray Kavukcuoglu · 2017
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Progressive growing of gans for improved quality, stability, and variation
Tero Karras, Timo Aila, Samuli Laine, and Jaakko Lehtinen · 2017
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Neural Discrete Representation Learning
Aaron van den Oord, Oriol Vinyals, and Koray Kavukcuoglu · 2017
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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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Scaling autoregressive video models
Dirk Weissenborn, Oscar Täckström, and Jakob Uszkoreit · 2020
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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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Efficient geometry-aware 3d generative adversarial networks
Eric R Chan, Connor Z Lin, Matthew A Chan, Koki Nagano, Boxiao Pan, Shalini De Mello, Orazio Gallo, Leonidas Guibas, Jonathan Tremblay, Sameh Khamis, et al · 2021
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Conceptual 12M: Pushing web-scale image-text pre-training to recognize long-tail visual concepts
Soravit Changpinyo, Piyush Sharma, Nan Ding, and Radu Soricut · 2021
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Diffusion models beat gans on image synthesis
Prafulla Dhariwal and Alexander Nichol · 2021
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Taming transformers for high-resolution image synthesis
Patrick Esser, Robin Rombach, and Bjorn Ommer · 2021
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Stylenerf: A style-based 3d-aware generator for high-resolution image synthesis
Jiatao Gu, Lingjie Liu, Peng Wang, and Christian Theobalt · 2021
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Improved denoising diffusion probabilistic models
Alexander Quinn Nichol and Prafulla Dhariwal · 2021
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Learning transferable visual models from natural language supervision
Hierarchical text-conditional image generation with clip latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 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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Pyramidal denoising diffusion probabilistic models
Dohoon Ryu and Jong Chul Ye · 2022
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Photorealistic text-to-image diffusion models with deep language understanding
Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily L Denton, Kamyar Ghasemipour, Raphael Gontijo Lopes, Burcu Karagol Ayan, Tim Salimans, et al · 2022
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Progressive distillation for fast sampling of diffusion models
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Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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Image super-resolution via iterative refinement
Chitwan Saharia, Jonathan Ho, William Chan, Tim Salimans, David J Fleet, and Mohammad Norouzi · 2021
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Nüwa: Visual synthesis pre-training for neural visual world creation, 2021
Chenfei Wu, Jian Liang, Lei Ji, Fan Yang, Yuejian Fang, Daxin Jiang, and Nan Duan · 2021
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ediffi: Text-to-image diffusion models with an ensemble of expert denoisers
Yogesh Balaji, Seungjun Nah, Xun Huang, Arash Vahdat, Jiaming Song, Karsten Kreis, Miika Aittala, Timo Aila, Samuli Laine, Bryan Catanzaro, et al · 2022
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Scaling instruction-finetuned language models, 2022
Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Eric Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, Albert Webson, Shixiang Shane Gu, Zhuyun Dai, Mirac Suzgun, Xinyun Chen, Aakanksha Chowdhery, Sharan Narang, Gaurav Mishra, Adams Yu, Vincent Zhao, Yanping Huang, Andrew Dai, Hongkun Yu, Slav Petrov, Ed H. Chi, Jeff Dean, Jacob Devlin, Adam Roberts, Denny Zhou, Quoc V. Le, and Jason Wei · 2022
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Make-a-scene: Scene-based text-to-image generation with human priors
Oran Gafni, Adam Polyak, Oron Ashual, Shelly Sheynin, Devi Parikh, and Yaniv Taigman · 2022
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f-dm: A multi-stage diffusion model via progressive signal transformation
Jiatao Gu, Shuangfei Zhai, Yizhe Zhang, Miguel Angel Bautista, and Josh Susskind · 2022
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Tim Salimans and Jonathan Ho · 2022
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Make-a-video: Text-to-video generation without text-video data, 2022
Uriel Singer, Adam Polyak, Thomas Hayes, Xi Yin, Jie An, Songyang Zhang, Qiyuan Hu, Harry Yang, Oron Ashual, Oran Gafni, Devi Parikh, Sonal Gupta, and Yaniv Taigman · 2022
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Scaling autoregressive models for content-rich text-to-image generation
Jiahui Yu, Yuanzhong Xu, Jing Yu Koh, Thang Luong, Gunjan Baid, Zirui Wang, Vijay Vasudevan, Alexander Ku, Yinfei Yang, Burcu Karagol Ayan, Ben Hutchinson, Wei Han, Zarana Parekh, Xin Li, Han Zhang, Jason Baldridge, and Yonghui Wu · 2022
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Single-stage diffusion nerf: A unified approach to 3d generation and reconstruction, 2023
Hansheng Chen, Jiatao Gu, Anpei Chen, Wei Tian, Zhuowen Tu, Lingjie Liu, and Hao Su · 2023
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On the importance of noise scheduling for diffusion models
Ting Chen · 2023
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Nerfdiff: Single-image view synthesis with nerf-guided distillation from 3d-aware diffusion
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Animatediff: Animate your personalized text-to-image diffusion models without specific tuning
Yuwei Guo, Ceyuan Yang, Anyi Rao, Yaohui Wang, Yu Qiao, Dahua Lin, and Bo Dai · 2023
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simple diffusion: End-to-end diffusion for high resolution images
Emiel Hoogeboom, Jonathan Heek, and Tim Salimans · 2023
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Scaling up gans for text-to-image synthesis
Minguk Kang, Jun-Yan Zhu, Richard Zhang, Jaesik Park, Eli Shechtman, Sylvain Paris, and Taesung Park · 2023
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Wuerstchen: Efficient pretraining of text-to-image models
Pablo Pernias, Dominic Rampas, and Marc Aubreville · 2023
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Sdxl: improving latent diffusion models for high-resolution image synthesis
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Generative modelling with inverse heat dissipation
Severi Rissanen, Markus Heinonen, and Arno Solin · 2023
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Raphael: Text-to-image generation via large mixture of diffusion paths
Zeyue Xue, Guanglu Song, Qiushan Guo, Boxiao Liu, Zhuofan Zong, Yu Liu, and Ping Luo · 2023
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Planner: Generating diversified paragraph via latent language diffusion model
Yizhe Zhang, Jiatao Gu, Zhuofeng Wu, Shuangfei Zhai, Josh Susskind, and Navdeep Jaitly · 2023
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