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Consistency models (CMs) are a powerful class of diffusion-based generative models optimized for fast sampling.
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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Learning multiple layers of features from tiny images
Alex Krizhevsky · 2009
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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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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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Progressive growing of gans for improved quality, stability, and variation
Tero Karras · 2017
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Attention is all you need
A Vaswani · 2017
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Large scale gan training for high fidelity natural image synthesis
Andrew Brock · 2018
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Multi-task learning as multi-objective optimization
Ozan Sener and Vladlen Koltun · 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
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On the variance of the adaptive learning rate and beyond
Liyuan Liu, Haoming Jiang, Pengcheng He, Weizhu Chen, Xiaodong Liu, Jianfeng Gao, and Jiawei Han · 2019
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Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, et al · 2019
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Generative modeling by estimating gradients of the data distribution
Yang Song and Stefano Ermon · 2019
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Fourier features let networks learn high frequency functions in low dimensional domains
Matthew Tancik, Pratul Srinivasan, Ben Mildenhall, Sara Fridovich-Keil, Nithin Raghavan, Utkarsh Singhal, Ravi Ramamoorthi, Jonathan Barron, and Ren Ng · 2020
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Diffusion models beat GANs on image synthesis
Prafulla Dhariwal and Alexander Quinn 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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Classifier-free diffusion guidance
Jonathan Ho and Tim Salimans · 2021
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Variational diffusion models
Diederik P Kingma, Tim Salimans, Ben Poole, and Jonathan Ho · 2021
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Knowledge distillation in iterative generative models for improved sampling speed
Eric Luhman and Troy Luhman · 2021
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Improved denoising diffusion probabilistic models
Alexander Quinn Nichol and Prafulla Dhariwal · 2021
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Maskgit: Masked generative image transformer
Huiwen Chang, Han Zhang, Lu Jiang, Ce Liu, and William T Freeman · 2022
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Flashattention: Fast and memory-efficient exact attention with io-awareness
Tri Dao, Dan Fu, Stefano Ermon, Atri Rudra, and Christopher Ré · 2022
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Imagen video: High definition video generation with diffusion models
Jonathan Ho, William Chan, Chitwan Saharia, Jay Whang, Ruiqi Gao, Alexey Gritsenko, Diederik P Kingma, Ben Poole, Mohammad Norouzi, David J Fleet, et al · 2022
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Scalable adaptive computation for iterative generation
Allan Jabri, David Fleet, and Ting Chen · 2022
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Planning with diffusion for flexible behavior synthesis
Michael Janner, Yilun Du, Joshua Tenenbaum, and Sergey Levine · 2022
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Elucidating the design space of diffusion-based generative models
Tero Karras, Miika Aittala, Timo Aila, and Samuli Laine · 2022
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Flow matching for generative modeling
Yaron Lipman, Ricky TQ Chen, Heli Ben-Hamu, Maximilian Nickel, and Matt Le · 2022
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Flow straight and fast: Learning to generate and transfer data with rectified flow
Xingchao Liu, Chengyue Gong, and Qiang Liu · 2022
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Non-denoising forward-time diffusions, 2022
Stefano Peluchetti · 2022
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Dreamfusion: Text-to-3d using 2d diffusion
Ben Poole, Ajay Jain, Jonathan T Barron, and Ben Mildenhall · 2022
Improved techniques for training consistency models
Yang Song and Prafulla Dhariwal · 2023
Later among the works it cites.
Consistency models
Yang Song, Prafulla Dhariwal, Mark Chen, and Ilya Sutskever · 2023
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Improving and generalizing flow-based generative models with minibatch optimal transport
Alexander Tong, Kilian Fatras, Nikolay Malkin, Guillaume Huguet, Yanlei Zhang, Jarrid Rector-Brooks, Guy Wolf, and Yoshua Bengio · 2023
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Language model beats diffusion–tokenizer is key to visual generation
Lijun Yu, José Lezama, Nitesh B Gundavarapu, Luca Versari, Kihyuk Sohn, David Minnen, Yong Cheng, Agrim Gupta, Xiuye Gu, Alexander G Hauptmann, et al · 2023
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Large-DiT-ImageNet
Alpha-VLLM · 2024
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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
Cited alongside, same era.
Progressive distillation for fast sampling of diffusion models
Tim Salimans and Jonathan Ho · 2022
Cited alongside, same era.
Stylegan-xl: Scaling stylegan to large diverse datasets
Axel Sauer, Katja Schwarz, and Andreas Geiger · 2022
Cited alongside, same era.
Diffusion-gan: Training gans with diffusion
Zhendong Wang, Huangjie Zheng, Pengcheng He, Weizhu Chen, and Mingyuan Zhou · 2022
Cited alongside, same era.
Tackling the generative learning trilemma with denoising diffusion GANs
Zhisheng Xiao, Karsten Kreis, and Arash Vahdat · 2022
Cited alongside, same era.
Stochastic interpolants: A unifying framework for flows and diffusions
Michael S Albergo, Nicholas M Boffi, and Eric Vanden-Eijnden · 2023
Cited alongside, same era.
Video generation models as world simulators
Tim Brooks, Bill Peebles, Connor Holmes, Will DePue, Yufei Guo, Li Jing, David Schnurr, Joe Taylor, Troy Luhman, Eric Luhman, Clarence Ng, Ricky Wang, and Aditya Ramesh · 2024
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Scaling rectified flow transformers for high-resolution image synthesis
Patrick Esser, Sumith Kulal, Andreas Blattmann, Rahim Entezari, Jonas Müller, Harry Saini, Yam Levi, Dominik Lorenz, Axel Sauer, Frederic Boesel, et al · 2024
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Fast timing-conditioned latent audio diffusion
Zach Evans, CJ Carr, Josiah Taylor, Scott H Hawley, and Jordi Pons · 2024
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Zhengyang Geng, Ashwini Pokle, William Luo, Justin Lin, and J Zico Kolter · 2024
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Jonathan Heek, Emiel Hoogeboom, and Tim Salimans · 2024
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Analyzing and improving the training dynamics of diffusion models
Tero Karras, Miika Aittala, Jaakko Lehtinen, Janne Hellsten, Timo Aila, and Samuli Laine · 2024
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Understanding diffusion objectives as the elbo with simple data augmentation
Diederik Kingma and Ruiqi Gao · 2024
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Optimal flow matching: Learning straight trajectories in just one step
Nikita Kornilov, Petr Mokrov, Alexander Gasnikov, and Alexander Korotin · 2024
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Autoregressive image generation without vector quantization
Tianhong Li, Yonglong Tian, He Li, Mingyang Deng, and Kaiming He · 2024
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Common diffusion noise schedules and sample steps are flawed
Shanchuan Lin, Bingchen Liu, Jiashi Li, and Xiao Yang · 2024
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Alleviating distortion in image generation via multi-resolution diffusion models
Qihao Liu, Zhanpeng Zeng, Ju He, Qihang Yu, Xiaohui Shen, and Liang-Chieh Chen · 2024
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Diff-instruct: A universal approach for transferring knowledge from pre-trained diffusion models
Weijian Luo, Tianyang Hu, Shifeng Zhang, Jiacheng Sun, Zhenguo Li, and Zhihua Zhang · 2024
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Sit: Exploring flow and diffusion-based generative models with scalable interpolant transformers
Nanye Ma, Mark Goldstein, Michael S Albergo, Nicholas M Boffi, Eric Vanden-Eijnden, and Saining Xie · 2024
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Multistep distillation of diffusion models via moment matching
Tim Salimans, Thomas Mensink, Jonathan Heek, and Emiel Hoogeboom · 2024
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Physics informed distillation for diffusion models
Joshua Tian Jin Tee, Kang Zhang, Hee Suk Yoon, Dhananjaya Nagaraja Gowda, Chanwoo Kim, and Chang D Yoo · 2024
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Dim: Diffusion mamba for efficient high-resolution image synthesis
Yao Teng, Yue Wu, Han Shi, Xuefei Ning, Guohao Dai, Yu Wang, Zhenguo Li, and Xihui Liu · 2024
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Prolificdreamer: High-fidelity and diverse text-to-3d generation with variational score distillation
Zhengyi Wang, Cheng Lu, Yikai Wang, Fan Bao, Chongxuan Li, Hang Su, and Jun Zhu · 2024
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Diffusion models without attention
Jing Nathan Yan, Jiatao Gu, and Alexander M Rush · 2024
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Consistency flow matching: Defining straight flows with velocity consistency
Ling Yang, Zixiang Zhang, Zhilong Zhang, Xingchao Liu, Minkai Xu, Wentao Zhang, Chenlin Meng, Stefano Ermon, and Bin Cui · 2024
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Score identity distillation: Exponentially fast distillation of pretrained diffusion models for one-step generation
Mingyuan Zhou, Huangjie Zheng, Zhendong Wang, Mingzhang Yin, and Hai Huang · 2024
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