Awesome-Visual-Diffusion-Models

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A collection of resources and papers on Visual Diffusion Models.

Awesome-Visual-Diffusion-Models
- Contents
- Landmark Papers
- Papers
  - Conference Papers
  - Journal Papers
  - Preprints
- Tutorials
- Blogs

Landmark Papers

Proceeding	Title	Assets
NeurIPS 2020	Denoising Diffusion Probabilistic Models Jonathan Ho, Ajay Jain, Pieter Abbeel	Paper TensorFlow PyTorch
NeurIPS 2021	Diffusion Models Beat GANs on Image Synthesis Prafulla Dhariwal, Alex Nichol	Paper PyTorch
NeurIPS 2022	Video Diffusion Models Jonathan Ho, Tim Salimans, Alexey Gritsenko, William Chan, Mohammad Norouzi, David J. Fleet	Paper

Papers

Conference Papers

Proceeding	Title	Assets
NeurIPS 2022	Flexible Diffusion Modeling of Long Videos William Harvey, Saeid Naderiparizi, Vaden Masrani, Christian Weilbach, Frank Wood	Paper
NeurIPS 2022	Denoising Diffusion Restoration Models Bahjat Kawar, Michael Elad, Stefano Ermon, Jiaming Song	Paper PyTorch Project
NeurIPS 2022	Elucidating the Design Space of Diffusion-Based Generative Models Tero Karras, Miika Aittala, Timo Aila, Samuli Laine	Paper
NeurIPS 2022	GENIE: Higher-Order Denoising Diffusion Solvers Tim Dockhorn, Arash Vahdat, Karsten Kreis	Paper Code Project
NeurIPS 2022	Improving Diffusion Models for Inverse Problems using Manifold Constraints Hyungjin Chung, Byeongsu Sim, Dohoon Ryu, Jong Chul Ye	Paper
NeurIPS 2022	Efficient Spatially Sparse Inference for Conditional GANs and Diffusion Models Muyang Li, Ji Lin, Chenlin Meng, Stefano Ermon, song han, Jun-Yan Zhu	Paper PyTorch
NeurIPS 2022	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, Jun Zhu	Paper PyTorch
NeurIPS 2022	Deep Equilibrium Approaches to Diffusion Models Ashwini Pokle, Zhengyang Geng, J Zico Kolter	Paper PyTorch
NeurIPS 2022	Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily Denton, Seyed Kamyar Seyed Ghasemipour, Burcu Karagol Ayan, S. Sara Mahdavi, Rapha Gontijo Lopes, Tim Salimans, Jonathan Ho, David J Fleet, Mohammad Norouzi	Paper
NeurIPS 2022	Unsupervised Representation Learning from Pre-trained Diffusion Probabilistic Models Zijian Zhang, Zhou Zhao, Zhijie Lin	Paper
NeurIPS 2022	Maximum Likelihood Training of Implicit Nonlinear Diffusion Models Dongjun Kim, Byeonghu Na, Se Jung Kwon, Dongsoo Lee, Wanmo Kang, Il-Chul Moon	Paper
NeurIPS 2022	Diffusion Visual Counterfactual Explanations Maximilian Augustin, Valentyn Boreiko, Francesco Croce, Matthias Hein	Paper PyTorch
NeurIPS 2022	MCVD-Masked Conditional Video Diffusion for Prediction, Generation, and Interpolation Vikram Voleti, Alexia Jolicoeur-Martineau, Christopher Pal	Paper Project
NeurIPS 2022	On Analyzing Generative and Denoising Capabilities of Diffusion-based Deep Generative Models Kamil Deja, Anna Kuzina, Tomasz Trzciński, Jakub M. Tomczak	Paper
NeurIPS 2022	Diffusion models as plug-and-play priors Alexandros Graikos, Nikolay Malkin, Nebojsa Jojic, Dimitris Samaras	Paper PyTorch
NeurIPS 2022	Riemannian Diffusion Models Chin-Wei Huang, Milad Aghajohari, Avishek Joey Bose, Prakash Panangaden, Aaron Courville	Paper
ECCV 2022	DiffuseMorph: Unsupervised Deformable Image Registration Using Diffusion Model Boah Kim, Inhwa Han, Jong Chul Ye	Paper PyTorch
ECCV 2022	Unleashing Transformers: Parallel Token Prediction with Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized Codes Sam Bond-Taylor, Peter Hessey, Hiroshi Sasaki, Toby P. Breckon, Chris G. Willcocks	Paper PyTorch
ECCV 2022	Entropy-Driven Sampling and Training Scheme for Conditional Diffusion Generation Guangcong Zheng, Shengming Li, Hui Wang, Taiping Yao, Yang Chen, Shouhong Ding, and Xi Li	Paper PyTorch
ECCV 2022	Compositional Visual Generation with Composable Diffusion Models Nan Liu, Shuang Li, Yilun Du, Antonio Torralba, Joshua B. Tenenbaum	Paper
ECCV 2022	Subspace Diffusion Generative Models Bowen Jing, Gabriele Corso, Renato Berlinghieri, Tommi Jaakkola	Paper PyTorch
ECCV 2022	Accelerating Score-based Generative Models with Preconditioned Diffusion Sampling Hengyuan Ma, Li Zhang, Xiatian Zhu, Jianfeng Feng	Paper PyTorch
ACM MM 2022	ProDiff: Progressive Fast Diffusion Model For High-Quality Text-to-Speech Rongjie Huang, Zhou Zhao, Huadai Liu, Jinglin Liu, Chenye Cui, Yi Ren	Paper
MICCAI 2022	Diffusion Deformable Model for 4D Temporal Medical Image Generation Boah Kim, Jong Chul Ye	Paper
ICML 2022	Diffusion bridges vector quantized Variational AutoEncoders Max Cohen, Guillaume Quispe, Sylvain Le Corff, Charles Ollion, Eric Moulines	Paper
ICML 2022	Maximum Likelihood Training for Score-based Diffusion ODEs by High Order Denoising Score Matching Cheng Lu, Kaiwen Zheng, Fan Bao, Chongxuan Li, Jianfei Chen, Jun Zhu
ICML 2022	Equivariant Diffusion for Molecule Generation in 3D Emiel Hoogeboom, Victor Garcia Satorras, Clément Vignac, Max Welling	Paper
ICML 2022	Soft Truncation: A Universal Training Technique of Score-based Diffusion Model for High Precision Score Estimation Dongjun Kim, Seungjae Shin, Kyungwoo Song, Wanmo Kang, Il-Chul Moon	Paper
ICML 2022	Latent Diffusion Energy-Based Model for Interpretable Text Modeling Peiyu Yu, Sirui Xie, Baoxiong Jia, Bo Pang, Ruiqi Gao, Yixin Zhu, Song-Chun Zhu, Ying Nian Wu
ICML 2022	Estimating the Optimal Covariance with Imperfect Mean in Diffusion Probabilistic Models Fan Bao, Chongxuan Li, Jiacheng Sun, Jun Zhu, Bo Zhang	Paper PyTorch
ICML 2022	Guided-TTS: A Diffusion Model for Text-to-Speech via Classifier Guidance Heeseung Kim, Sungwon Kim, Sungroh Yoon	Paper
ICML 2022	GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models Alex Nichol, Prafulla Dhariwal, Aditya Ramesh, Pranav Shyam, Pamela Mishkin, Bob McGrew, Ilya Sutskever, Mark Chen	Paper
ICML 2022	Diffusion Models for Adversarial Purification Weili Nie, Brandon Guo, Yujia Huang, Chaowei Xiao, Arash Vahdat, Anima Anandkumar	Paper Project
IJCAI 2022	FastDiff: A Fast Conditional Diffusion Model for High-Quality Speech Synthesis Rongjie Huang, Max W. Y. Lam, Jun Wang, Dan Su, Dong Yu, Yi Ren, Zhou Zhao	Paper
CVPR 2022	Diffusion Autoencoders: Toward a Meaningful and Decodable Representation Konpat Preechakul, Nattanat Chatthee, Suttisak Wizadwongsa, Supasorn Suwajanakorn	Paper Project
CVPR 2022	Blended Diffusion: Text-driven Editing of Natural Images Omri Avrahami, Dani Lischinski, Ohad Fried	Paper PyTorch Project
CVPR 2022	Vector Quantized Diffusion Model for Text-to-Image Synthesis Shuyang Gu, Dong Chen, Jianmin Bao, Fang Wen, Bo Zhang, Dongdong Chen, Lu Yuan, Baining Guo	Paper PyTorch
CVPR 2022	DiffusionCLIP: Text-guided Image Manipulation Using Diffusion Models Gwanghyun Kim, Taesung Kwon, Jong Chul Ye	Paper PyTorch
CVPR 2022	RePaint: Inpainting using Denoising Diffusion Probabilistic Models Andreas Lugmayr, Martin Danelljan, Andres Romero, Fisher Yu, Radu Timofte, Luc Van Gool	Paper PyTorch
CVPR 2022	High-Resolution Image Synthesis with Latent Diffusion Models Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, Björn Ommer	Paper PyTorch
CVPR 2022	Dynamic Dual-Output Diffusion Models Yaniv Benny, Lior Wolf	Paper
CVPR 2022	Perception Prioritized Training of Diffusion Models Jooyoung Choi, Jungbeom Lee, Chaehun Shin, Sungwon Kim, Hyunwoo Kim, Sungroh Yoon	Paper PyTorch
CVPR 2022	Generating High Fidelity Data from Low-density Regions using Diffusion Models Vikash Sehwag, Caner Hazirbas, Albert Gordo, Firat Ozgenel, Cristian Canton Ferrer	Paper
CVPR 2022	Come-Closer-Diffuse-Faster: Accelerating Conditional Diffusion Models for Inverse Problems through Stochastic Contraction Hyungjin Chung, Byeongsu Sim, Jong Chul Ye	Paper
CVPRW 2022	On Conditioning the Input Noise for Controlled Image Generation with Diffusion Models Vedant Singh, Surgan Jandial, Ayush Chopra, Siddharth Ramesh, Balaji Krishnamurthy, Vineeth N. Balasubramanian	Paper
ICLR 2022	Analytic-DPM: an Analytic Estimate of the Optimal Reverse Variance in Diffusion Probabilistic Models Fan Bao, Chongxuan Li, Jun Zhu, Bo Zhang	Paper PyTorch
ICLR 2022	SDEdit: Image Synthesis and Editing with Stochastic Differential Equations Chenlin Meng, Yang Song, Jiaming Song, Jiajun Wu, Jun-Yan Zhu, Stefano Ermon	Paper PyTorch Project
ICLR 2022	Denoising Likelihood Score Matching for Conditional Score-based Data Generation Chen-Hao Chao, Wei-Fang Sun, Bo-Wun Cheng, Yi-Chen Lo, Chia-Che Chang, Yu-Lun Liu, Yu-Lin Chang, Chia-Ping Chen, Chun-Yi Lee	Paper Code
ICLR 2022	Learning Fast Samplers for Diffusion Models by Differentiating Through Sample Quality Daniel Watson, William Chan, Jonathan Ho, Mohammad Norouzi	Paper
ICLR 2022	Score-Based Generative Modeling with Critically-Damped Langevin Diffusion Tim Dockhorn, Arash Vahdat, Karsten Kreis	Paper PyTorch
ICLR 2022	Progressive Distillation for Fast Sampling of Diffusion Models Tim Salimans, Jonathan Ho	Paper TensorFlow
ICLR 2022	Autoregressive Diffusion Models Emiel Hoogeboom, Alexey A. Gritsenko, Jasmijn Bastings, Ben Poole, Rianne van den Berg, Tim Salimans	Paper
ICLR 2022	Pseudo Numerical Methods for Diffusion Models on Manifolds Luping Liu, Yi Ren, Zhijie Lin, Zhou Zhao	Paper PyTorch
ICLR 2022	Learning Fast Samplers for Diffusion Models by Differentiating Through Sample Quality Daniel Watson, William Chan, Jonathan Ho, Mohammad Norouzi	Paper
ICLR 2022	Label-Efficient Semantic Segmentation with Diffusion Models Dmitry Baranchuk, Andrey Voynov, Ivan Rubachev, Valentin Khrulkov, Artem Babenko	Paper PyTorch
ICLR 2022	Step-unrolled Denoising Autoencoders for Text Generation Nikolay Savinov, Junyoung Chung, Mikolaj Binkowski, Erich Elsen, Aaron van den Oord	Paper PyTorch
ICLR 2022	Tackling the Generative Learning Trilemma with Denoising Diffusion GANs Zhisheng Xiao, Karsten Kreis, Arash Vahdat	Paper PyTorch Project
ICLR 2022	PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Dependent Adaptive Prior Sang-gil Lee, Heeseung Kim, Chaehun Shin, Xu Tan, Chang Liu, Qi Meng, Tao Qin, Wei Chen, Sungroh Yoon, Tie-Yan Liu	Paper
ICLR 2022	A Conditional Point Diffusion-Refinement Paradigm for 3D Point Cloud Completion Zhaoyang Lyu, Zhifeng Kong, Xudong Xu, Liang Pan, Dahua Lin	Paper PyTorch
ICLR 2022	BDDM: Bilateral Denoising Diffusion Models for Fast and High-Quality Speech Synthesis Max W. Y. Lam, Jun Wang, Dan Su, Dong Yu	Paper PyTorch
MIDL 2022	Diffusion Models for Implicit Image Segmentation Ensembles Julia Wolleb, Robin Sandkuehler, Florentin Bieder, Philippe Valmaggia, Philippe C. Cattin	Paper PyTorch
NeurIPS 2021	Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions Emiel Hoogeboom, Didrik Nielsen, Priyank Jaini, Patrick Forré, Max Welling	Paper PyTorch
NeurIPS 2021	Diffusion Normalizing Flow Qinsheng Zhang, Yongxin Chen	Paper Code
NeurIPS 2021	ImageBART: Bidirectional Context with Multinomial Diffusion for Autoregressive Image Synthesis Patrick Esser, Robin Rombach, Andreas Blattmann, Bjorn Ommer	Paper PyTorch Project
NeurIPS 2021	Maximum Likelihood Training of Score-Based Diffusion Models Yang Song, Conor Durkan, Iain Murray, Stefano Ermon	Paper TensorFlow
NeurIPS 2021	Variational Diffusion Models Diederik P. Kingma, Tim Salimans, Ben Poole, Jonathan Ho	Paper TensorFlow
NeurIPS 2021	D2C: Diffusion-Decoding Models for Few-Shot Conditional Generation Abhishek Sinha, Jiaming Song, Chenlin Meng, Stefano Ermon	Paper PyTorch
NeurIPS 2021	Structured Denoising Diffusion Models in Discrete State-Spaces Jacob Austin, Daniel D. Johnson, Jonathan Ho, Daniel Tarlow, Rianne van den Berg	Paper
NeurIPS 2021	CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation Yusuke Tashiro, Jiaming Song, Yang Song, Stefano Ermon	Paper PyTorch
ICCV 2021	ILVR: Conditioning Method for Denoising Diffusion Probabilistic Models Jooyoung Choi, Sungwon Kim, Yonghyun Jeong, Youngjune Gwon, Sungroh Yoon	Paper PyTorch
ICML 2021	Improved Denoising Diffusion Probabilistic Models Alex Nichol, Prafulla Dhariwal	Paper PyTorch
CVPR 2021	Diffusion Probabilistic Models for 3D Point Cloud Generation Shitong Luo, Wei Hu	Paper PyTorch
ICLR 2021	Denoising Diffusion Implicit Models Jiaming Song, Chenlin Meng, Stefano Ermon	Paper PyTorch

Journal Papers

Journal	Title	Assets
JMLR 2022	Cascaded Diffusion Models for High Fidelity Image Generation Jonathan Ho, Chitwan Saharia, William Chan, David J. Fleet, Mohammad Norouzi, Tim Salimans	Paper Project
Neurocomputing 2022	SRDiff: Single Image Super-Resolution with Diffusion Probabilistic Models Haoying Li, Yifan Yang, Meng Chang, Huajun Feng, Zhihai Xu, Qi Li, Yueting Chen	Paper

Preprints

Preprints	Title	Assets
arXiv 2022	High-Frequency Space Diffusion Models for Accelerated MRI Chentao Cao, Zhuo-Xu Cui, Shaonan Liu, Dong Liang, Yanjie Zhu	Paper
arXiv 2022	Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning Ting Chen, Ruixiang Zhang, Geoffrey Hinton	Paper
arXiv 2022	Pyramidal Denoising Diffusion Probabilistic Models Dohoon Ryu, Jong Chul Ye	Paper
arXiv 2022	DeScoD-ECG: Deep Score-Based Diffusion Model for ECG Baseline Wander and Noise Removal Huayu Li, Gregory Ditzler, Janet Roveda, Ao Li	Paper
arXiv 2022	Restoring Vision in Adverse Weather Conditions with Patch-Based Denoising Diffusion Models Ozan Özdenizci, Robert Legenstein	Paper
arXiv 2022	Text-Guided Synthesis of Artistic Images with Retrieval-Augmented Diffusion Models Robin Rombach, Andreas Blattmann, Björn Ommer	Paper
arXiv 2022	Progressive Deblurring of Diffusion Models for Coarse-to-Fine Image Synthesis Sangyun Lee, Hyungjin Chung, Jaehyeon Kim, Jong Chul Ye	Paper
arXiv 2022	Deep Diffusion Models for Seismic Processing Ricard Durall, Ammar Ghanim, Mario Fernandez, Norman Ettrich, Janis Keuper	Paper
arXiv 2022	Diffsound: Discrete Diffusion Model for Text-to-sound Generation Dongchao Yang, Jianwei Yu, Helin Wang, Wen Wang, Chao Weng, Yuexian Zou, Dong Yu	Paper
arXiv 2022	Non-Uniform Diffusion Models Georgios Batzolis, Jan Stanczuk, Carola-Bibiane Schönlieb, Christian Etmann	Paper
arXiv 2022	Diffsound: Discrete Diffusion Model for Text-to-sound Generation Dongchao Yang, Jianwei Yu, Helin Wang, Wen Wang, Chao Weng, Yuexian Zou, Dong Yu	Paper
arXiv 2022	Adaptive Diffusion Priors for Accelerated MRI Reconstruction Salman UH Dar, Şaban Öztürk, Yilmaz Korkmaz, Gokberk Elmas, Muzaffer Özbey, Alper Güngör, Tolga Çukur	Paper
arXiv 2022	Unsupervised Medical Image Translation with Adversarial Diffusion Models Muzaffer Özbey, Salman UH Dar, Hasan A Bedel, Onat Dalmaz, Şaban Özturk, Alper Güngör, Tolga Çukur	Paper
arXiv 2022	Threat Model-Agnostic Adversarial Defense using Diffusion Models Tsachi Blau, Roy Ganz, Bahjat Kawar, Alex Bronstein, Michael Elad	Paper
arXiv 2022	Improving Diffusion Model Efficiency Through Patching Troy Luhman, Eric Luhman	Paper
arXiv 2022	Semantic Image Synthesis via Diffusion Models Weilun Wang, Jianmin Bao, Wengang Zhou, Dongdong Chen, Dong Chen, Lu Yuan, Houqiang Li	Paper
arXiv 2022	DDPM-CD: Remote Sensing Change Detection using Denoising Diffusion Probabilistic Models Wele Gedara Chaminda Bandara, Nithin Gopalakrishnan Nair, Vishal M. Patel	Paper PyTorch
arXiv 2022	Guided Diffusion Model for Adversarial Purification from Random Noise Quanlin Wu, Hang Ye, Yuntian Gu	Paper
arXiv 2022	A Flexible Diffusion Model Weitao Du, Tao Yang, He Zhang, Yuanqi Du	Paper
arXiv 2022	CARD: Classification and Regression Diffusion Models Xizewen Han, Huangjie Zheng, Mingyuan Zhou	Paper
arXiv 2022	Diffusion Models for Video Prediction and Infilling Tobias Höppe, Arash Mehrjou, Stefan Bauer, Didrik Nielsen, Andrea Dittadi	Paper
arXiv 2022	gDDIM: Generalized denoising diffusion implicit models Qinsheng Zhang, Molei Tao, Yongxin Chen	Paper Code
arXiv 2022	How Much is Enough? A Study on Diffusion Times in Score-based Generative Models Giulio Franzese, Simone Rossi, Lixuan Yang, Alessandro Finamore, Dario Rossi, Maurizio Filippone, Pietro Michiardi	Paper
arXiv 2022	Image Generation with Multimodal Priors using Denoising Diffusion Probabilistic Models Nithin Gopalakrishnan Nair, Wele Gedara Chaminda Bandara, Vishal M Patel	Paper
arXiv 2022	SAR Despeckling using a Denoising Diffusion Probabilistic Model Malsha V. Perera, Nithin Gopalakrishnan Nair, Wele Gedara Chaminda Bandara, Vishal M. Patel	Paper
arXiv 2022	Diffusion probabilistic modeling of protein backbones in 3D for the motif-scaffolding problem Brian L. Trippe, Jason Yim, Doug Tischer, Tamara Broderick, David Baker, Regina Barzilay, Tommi Jaakkola	Paper
arXiv 2022	Fast Unsupervised Brain Anomaly Detection and Segmentation with Diffusion Models Walter H. L. Pinaya, Mark S. Graham, Robert Gray, Pedro F Da Costa, Petru-Daniel Tudosiu, Paul Wright, Yee H. Mah, Andrew D. MacKinnon, James T. Teo, Rolf Jager, David Werring, Geraint Rees, Parashkev Nachev, Sebastien Ourselin, M. Jorge Cardoso	Paper
arXiv 2022	Blended Latent Diffusion Omri Avrahami, Ohad Fried, Dani Lischinski	Paper PyTorch Project
arXiv 2022	Diffusion-GAN: Training GANs with Diffusion Zhendong Wang, Huangjie Zheng, Pengcheng He, Weizhu Chen, Mingyuan Zhou	Paper
arXiv 2022	Improving Diffusion Models for Inverse Problems using Manifold Constraints Hyungjin Chung, Byeongsu Sim, Dohoon Ryu, Jong Chul Ye	Paper
arXiv 2022	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, Jun Zhu	Paper
arXiv 2022	Improved Vector Quantized Diffusion Models Zhicong Tang, Shuyang Gu, Jianmin Bao, Dong Chen, Fang Wen	Paper PyTorch
arXiv 2022	Few-Shot Diffusion Models Giorgio Giannone, Didrik Nielsen, Ole Winther	Paper PyTorch
arXiv 2022	Protein Structure and Sequence Generation with Equivariant Denoising Diffusion Probabilistic Models Namrata Anand, Tudor Achim	Paper Project
arXiv 2022	Guided Diffusion Model for Adversarial Purification Jinyi Wang, Zhaoyang Lyu, Dahua Lin, Bo Dai, Hongfei Fu	Paper
arXiv 2022	Pretraining is All You Need for Image-to-Image Translation Tengfei Wang, Ting Zhang, Bo Zhang, Hao Ouyang, Dong Chen, Qifeng Chen, Fang Wen	Paper PyTorch Project
arXiv 2022	Accelerating Diffusion Models via Early Stop of the Diffusion Process Zhaoyang Lyu, Xudong XU, Ceyuan Yang, Dahua Lin, Bo Dai	Paper
arXiv 2022	Fast Sampling of Diffusion Models with Exponential Integrator Qinsheng Zhang, Yongxin Chen	Paper
arXiv 2022	Retrieval-Augmented Diffusion Models Andreas Blattmann, Robin Rombach, Kaan Oktay, Björn Ommer	Paper
arXiv 2022	Hierarchical Text-Conditional Image Generation with CLIP Latents Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, Mark Chen	Paper
arXiv 2022	Truncated Diffusion Probabilistic Models Huangjie Zheng, Pengcheng He, Weizhu Chen, Mingyuan Zhou	Paper
arXiv 2022	The Swiss Army Knife for Image-to-Image Translation: Multi-Task Diffusion Models Julia Wolleb, Robin Sandkühler, Florentin Bieder, Philippe C. Cattin	Paper
arXiv 2022	Dual Diffusion Implicit Bridges for Image-to-Image Translation Xuan Su, Jiaming Song, Chenlin Meng, Stefano Ermon	Paper
arXiv 2022	DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents Kushagra Pandey, Avideep Mukherjee, Piyush Rai, Abhishek Kumar	Paper PyTorch
arXiv 2022	Diffusion Probabilistic Modeling for Video Generation Ruihan Yang, Prakhar Srivastava, Stephan Mandt	Paper
arXiv 2021	More Control for Free! Image Synthesis with Semantic Diffusion Guidance Xihui Liu, Dong Huk Park, Samaneh Azadi, Gong Zhang, Arman Chopikyan, Yuxiao Hu, Humphrey Shi, Anna Rohrbach, Trevor Darrell	Paper Project
arXiv 2021	DiffuseMorph: Unsupervised Deformable Image Registration Along Continuous Trajectory Using Diffusion Models Boah Kim, Inhwa Han, Jong Chul Ye	Paper
arXiv 2021	Global Context with Discrete Diffusion in Vector Quantised Modelling for Image Generation Minghui Hu, Yujie Wang, Tat-Jen Cham, Jianfei Yang, P.N.Suganthan	Paper
arXiv 2021	Conditional Image Generation with Score-Based Diffusion Models Georgios Batzolis, Jan Stanczuk, Carola-Bibiane Schönlieb, Christian Etmann	Paper
arXiv 2021	SegDiff: Image Segmentation with Diffusion Probabilistic Models Tomer Amit, Eliya Nachmani, Tal Shaharbany, Lior Wolf	Paper
arXiv 2021	Palette: Image-to-Image Diffusion Models Chitwan Saharia, William Chan, Huiwen Chang, Chris A. Lee, Jonathan Ho, Tim Salimans, David J. Fleet, Mohammad Norouzi	Paper Project
arXiv 2021	UNIT-DDPM: UNpaired Image Translation with Denoising Diffusion Probabilistic Models Hiroshi Sasaki, Chris G. Willcocks, Toby P. Breckon	Paper

Tutorials

Denoising Diffusion-based Generative Modeling: Foundations and Applications, CVPR 2022. Website

Blogs

What are Diffusion Models? Lilian Weng. Website

Awesome-Visual-Diffusion-Models
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Metadata

Awesome-Visual-Diffusion-Models

Contents

Landmark Papers

Papers

Conference Papers

Journal Papers

Preprints

Tutorials

Blogs

← Metadata

Owner

Metadata

Awesome-Visual-Diffusion-Models Awesome-Visual-Diffusion-Models copied to clipboard

Metadata

Awesome-Visual-Diffusion-Models

Contents

Landmark Papers

Papers

Conference Papers

Journal Papers

Preprints

Tutorials

Blogs

← Metadata

Owner

Metadata

Awesome-Visual-Diffusion-Models
Awesome-Visual-Diffusion-Models copied to clipboard