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Diffusion Transformers have recently demonstrated unprecedented generative capabilities for various tasks.
Cache memories
Alan Jay Smith · 1982
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U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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Improved techniques for training gans
Tim Salimans, Ian Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, and Xi Chen · 2016
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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
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Improved precision and recall metric for assessing generative models
Tuomas Kynkäänniemi, Tero Karras, Samuli Laine, Jaakko Lehtinen, and Timo Aila · 2019
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Generative modeling by estimating gradients of the data distribution
Yang Song and Stefano Ermon · 2019
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An image is worth 16x16 words: Transformers for image recognition at scale
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Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Jiaming Song, Chenlin Meng, and Stefano Ermon · 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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Diffusion models beat gans on image synthesis
Prafulla Dhariwal and Alexander Nichol · 2021
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Score-based generative modeling with critically-damped langevin diffusion
Tim Dockhorn, Arash Vahdat, and Karsten Kreis · 2021
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Gotta go fast when generating data with score-based models
Alexia Jolicoeur-Martineau, Ke Li, Rémi Piché-Taillefer, Tal Kachman, and Ioannis Mitliagkas · 2021
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Generating images with sparse representations
Charlie Nash, Jacob Menick, Sander Dieleman, and Peter W Battaglia · 2021
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Analytic-dpm: an analytic estimate of the optimal reverse variance in diffusion probabilistic models
Fan Bao, Chongxuan Li, Jun Zhu, and Bo Zhang · 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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Pseudo numerical methods for diffusion models on manifolds
Luping Liu, Yi Ren, Zhijie Lin, and Zhou Zhao · 2022
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Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps
Cheng Lu, Yuhao Zhou, Fan Bao, Jianfei Chen, Chongxuan Li, and Jun Zhu · 2022
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Dpm-solver++: Fast solver for guided sampling of diffusion probabilistic models
Cheng Lu, Yuhao Zhou, Fan Bao, Jianfei Chen, Chongxuan Li, and Jun Zhu · 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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Progressive distillation for fast sampling of diffusion models
Tim Salimans and Jonathan Ho · 2022
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Your vit is secretly a hybrid discriminative-generative diffusion model
Xiulong Yang, Sheng-Min Shih, Yinlin Fu, Xiaoting Zhao, and Shihao Ji · 2022
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Fast sampling of diffusion models with exponential integrator
Qinsheng Zhang and Yongxin Chen · 2022
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gddim: Generalized denoising diffusion implicit models
Qinsheng Zhang, Molei Tao, and Yongxin Chen · 2022
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All are worth words: A vit backbone for diffusion models
Fan Bao, Shen Nie, Kaiwen Xue, Yue Cao, Chongxuan Li, Hang Su, and Jun Zhu · 2023
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Ziang Cao, Fangzhou Hong, Tong Wu, Liang Pan, and Ziwei Liu · 2023
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Gentron: Delving deep into diffusion transformers for image and video generation
Shoufa Chen, Mengmeng Xu, Jiawei Ren, Yuren Cong, Sen He, Yanping Xie, Animesh Sinha, Ping Luo, Tao Xiang, and Juan-Manuel Perez-Rua · 2023
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0.1% data makes segment anything slim
Zigeng Chen, Gongfan Fang, Xinyin Ma, and Xinchao Wang · 2023
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Masked diffusion transformer is a strong image synthesizer
Shanghua Gao, Pan Zhou, Ming-Ming Cheng, and Shuicheng Yan · 2023
Diffusion probabilistic model made slim
Xingyi Yang, Daquan Zhou, Jiashi Feng, and Xinchao Wang · 2023
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Distribution shift inversion for out-of-distribution prediction
Runpeng Yu, Songhua Liu, Xingyi Yang, and Xinchao Wang · 2023
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Mobilediffusion: Subsecond text-to-image generation on mobile devices
Yang Zhao, Yanwu Xu, Zhisheng Xiao, and Tingbo Hou · 2023
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Fast training of diffusion models with masked transformers
Hongkai Zheng, Weili Nie, Arash Vahdat, and Anima Anandkumar · 2023
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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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Ptqd: Accurate post-training quantization for diffusion models
Yefei He, Luping Liu, Jing Liu, Weijia Wu, Hong Zhou, and Bohan Zhuang · 2023
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Fast inference through the reuse of attention maps in diffusion models
Rosco Hunter, Łukasz Dudziak, Mohamed S Abdelfattah, Abhinav Mehrotra, Sourav Bhattacharya, and Hongkai Wen · 2023
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U-dit tts: U-diffusion vision transformer for text-to-speech
Xin Jing, Yi Chang, Zijiang Yang, Jiangjian Xie, Andreas Triantafyllopoulos, and Bjoern W Schuller · 2023
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Bk-sdm: Architecturally compressed stable diffusion for efficient text-to-image generation
Bo-Kyeong Kim, Hyoung-Kyu Song, Thibault Castells, and Shinkook Choi · 2023
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Faster diffusion: Rethinking the role of unet encoder in diffusion models
Senmao Li, Taihang Hu, Fahad Shahbaz Khan, Linxuan Li, Shiqi Yang, Yaxing Wang, Ming-Ming Cheng, and Jian Yang · 2023
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Q-diffusion: Quantizing diffusion models
Xiuyu Li, Yijiang Liu, Long Lian, Huanrui Yang, Zhen Dong, Daniel Kang, Shanghang Zhang, and Kurt Keutzer · 2023
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Oms-dpm: Optimizing the model schedule for diffusion probabilistic models
Enshu Liu, Xuefei Ning, Zinan Lin, Huazhong Yang, and Yu Wang · 2023
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Scaling rectified flow transformers for high-resolution image synthesis
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Sdxl-lightning: Progressive adversarial diffusion distillation
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Linfusion: 1 gpu, 1 minute, 16k image
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Dit-3d: Exploring plain diffusion transformers for 3d shape generation
Shentong Mo, Enze Xie, Ruihang Chu, Lanqing Hong, Matthias Niessner, and Zhenguo Li · 2024
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T-stitch: Accelerating sampling in pre-trained diffusion models with trajectory stitching
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Mixture-of-depths: Dynamically allocating compute in transformer-based language models
David Raposo, Sam Ritter, Blake Richards, Timothy Lillicrap, Peter Conway Humphreys, and Adam Santoro · 2024
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Litefocus: Accelerated diffusion inference for long audio synthesis
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Sparsedm: Toward sparse efficient diffusion models, 2024
Kafeng Wang, Jianfei Chen, He Li, Zhenpeng Mi, and Jun Zhu · 2024
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Hash3d: Training-free acceleration for 3d generation
Xingyi Yang and Xinchao Wang · 2024
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Neural lineage
Runpeng Yu and Xinchao Wang · 2024
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Dingkun Zhang, Sijia Li, Chen Chen, Qingsong Xie, and Haonan Lu · 2024
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Cross-attention makes inference cumbersome in text-to-image diffusion models, 2024
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