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This repository contains a collection of resources and papers on Low-level Diffusion Model.
Recent rise of diffusion-based models
Maciej Domagała
[Website]
06 Jun 2022
Introduction to Diffusion Models for Machine Learning
Ryan O'Connor
[Website]
12 May 2022
Improving Diffusion Models as an Alternative To GANs
Arash Vahdat and Karsten Kreis
[Website-Part 1] [Website-Part 2]
26 Apr 2022
An introduction to Diffusion Probabilistic Models
Ayan Das
[Website]
04 Dec 2021
Introduction to deep generative modeling: Diffusion-based Deep Generative Models
Jakub Tomczak
[Website]
30 Aug 2021
What are Diffusion Models?
Lilian Weng
[Website]
11 Jul 2021
Diffusion Models as a kind of VAE
Angus Turner
[Website]
29 June 2021
Generative Modeling by Estimating Gradients of the Data Distribution
Yang Song
[Website]
5 May 2021
A Connection Between Score Matching and Denoising Autoencoders
Pascal Vincent
Neural Computation 2011. [Paper]
7 Jul 2011
Bayesian Learning via Stochastic Gradient Langevin Dynamics
Max Welling, Yee Whye Teh
ICML 2011. [Paper] [Github]
20 Apr 2022
What are Diffusion Models?
Ari Seff
[Video]
20 Apr 2022
Diffusion models explained
AI Coffee Break with Letitia
[Video]
23 Mar 2022
Diffusion Probabilistic Models
Jascha Sohl-Dickstein, MIT 6.S192 - Lecture 22
[Video]
19 April 2022
Entropy-driven Sampling and Training Scheme for Conditional Diffusion Generation
Shengming Li, Guangcong Zheng, Hui Wang, Taiping Yao, Yang Chen, Shoudong Ding, Xi Li
arXiv 2022. [Paper]
23 Jun 2022
Diffusion models as plug-and-play priors
Alexandros Graikos, Nikolay Malkin, Nebojsa Jojic, Dimitris Samaras
arXiv 2022. [Paper]
17 June 2022
A Flexible Diffusion Model
Weitao Du, Tao Yang, He Zhang, Yuanqi Du
arXiv 2022. [Paper]
17 Jun 2022
Lossy Compression with Gaussian Diffusion
Lucas Theis, Tim Salimans, Matthew D. Hoffman, Fabian Mentzer
arXiv 2022. [Paper]
17 Jun 2022
Maximum Likelihood Training for Score-Based Diffusion ODEs by High-Order Denoising Score Matching
Cheng Lu, Kaiwen Zheng, Fan Bao, Jianfei Chen, Chongxuan Li, Jun Zhu
ICML 2022. [Paper]
16 Jun 2022
Estimating the Optimal Covariance with Imperfect Mean in Diffusion Probabilistic Models
Fan Bao, Chongxuan Li, Jiacheng Sun, Jun Zhu, Bo Zhang
ICML 2022. [Paper] [Github]
15 Jun 2022
Discrete Contrastive Diffusion for Cross-Modal and Conditional Generation
Ye Zhu, Yu Wu, Kyle Olszewski, Jian Ren, Sergey Tulyakov, Yan Yan
arXiv 2022. [Paper] [Github]
15 Jun 2022
gDDIM: Generalized denoising diffusion implicit models
Qinsheng Zhang, Molei Tao, Yongxin Chen
arXiv 2022. [Paper] [Github]
11 Jun 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
arXiv 2022. [Paper]
10 Jun 2022
Image Generation with Multimodal Priors using Denoising Diffusion Probabilistic Models
Nithin Gopalakrishnan Nair, Wele Gedara Chaminda Bandara, Vishal M Patel
arXiv 2022. [Paper]
10 Jun 2022
Accelerating Score-based Generative Models for High-Resolution Image Synthesis
Hengyuan Ma, Li Zhang, Xiatian Zhu, Jingfeng Zhang, Jianfeng Feng
arXiv 2022. [Paper]
8 Jun 2022
Diffusion-GAN: Training GANs with Diffusion
Zhendong Wang, Huangjie Zheng, Pengcheng He, Weizhu Chen, Mingyuan Zhou
arXiv 2022. [Paper]
5 Jun 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
arXiv 2022. [Paper]
2 Jun 2022
Elucidating the Design Space of Diffusion-Based Generative Models
Tero Karras, Miika Aittala, Timo Aila, Samuli Laine
arXiv 2022. [Paper]
1 Jun 2022
On Analyzing Generative and Denoising Capabilities of Diffusion-based Deep Generative Models
Kamil Deja, Anna Kuzina, Tomasz Trzciński, Jakub M. Tomczak
arXiv 2022. [Paper]
31 May 2022
Few-Shot Diffusion Models
Giorgio Giannone, Didrik Nielsen, Ole Winther
arXiv 2022. [Paper]
30 May 2022
A Continuous Time Framework for Discrete Denoising Models
Andrew Campbell, Joe Benton, Valentin De Bortoli, Tom Rainforth, George Deligiannidis, Arnaud Doucet
arXiv 2022. [Paper]
30 May 2022
Maximum Likelihood Training of Implicit Nonlinear Diffusion Models
Dongjun Kim, Byeonghu Na, Se Jung Kwon, Dongsoo Lee, Wanmo Kang, Il-Chul Moon
arXiv 2022. [Paper]
27 May 2022
Accelerating Diffusion Models via Early Stop of the Diffusion Process
Zhaoyang Lyu, Xudong XU, Ceyuan Yang, Dahua Lin, Bo Dai
ICML 2022. [Paper]
25 May 2022
On Conditioning the Input Noise for Controlled Image Generation with Diffusion Models
Vedant Singh1, Surgan Jandial1, Ayush Chopra, Siddharth Ramesh, Balaji Krishnamurthy, Vineeth N. Balasubramanian
arxiv 2022. [Paper]
8 May 2022
Subspace Diffusion Generative Models
Bowen Jing, Gabriele Corso, Renato Berlinghieri, Tommi Jaakkola
arXiv 2022. [Paper] [Github]
3 May 2022
Fast Sampling of Diffusion Models with Exponential Integrator
Qinsheng Zhang, Yongxin Chen
arXiv 2022. [Paper]
29 Apr 2022
Retrieval-Augmented Diffusion Models
Andreas Blattmann1, Robin Rombach1, Kaan Oktay, Björn Ommer
arXiv 2022. [Paper]
25 Apr 2022
Perception Prioritized Training of Diffusion Models
Jooyoung Choi, Jungbeom Lee, Chaehun Shin, Sungwon Kim, Hyunwoo Kim, Sungroh Yoon
arXiv 2022. [Paper] [Github]
1 Apr 2022
Generating High Fidelity Data from Low-density Regions using Diffusion Models
Vikash Sehwag, Caner Hazirbas, Albert Gordo, Firat Ozgenel, Cristian Canton Ferrer
arXiv 2022. [Paper]
31 Mar 2022
Diffusion Models for Counterfactual Explanations
Guillaume Jeanneret, Loïc Simon, Frédéric Jurie
arXiv 2022. [Paper]
29 Mar 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
ICLR 2022. [Paper]
27 Mar 2022
Dynamic Dual-Output Diffusion Models
Yaniv Benny, Lior Wolf
arXiv 2022. [Paper]
8 Mar 2022
Conditional Simulation Using Diffusion Schrödinger Bridges
Yuyang Shi, Valentin De Bortoli, George Deligiannidis, Arnaud Doucet
arXiv 2022. [Paper]
27 Feb 2022
Diffusion Causal Models for Counterfactual Estimation
Pedro Sanchez, Sotirios A. Tsaftaris
PMLR 2022. [Paper]
21 Feb 2022
Pseudo Numerical Methods for Diffusion Models on Manifolds
Luping Liu, Yi Ren, Zhijie Lin, Zhou Zhao
ICLR 2022. [Paper] [Github]
20 Feb 2022
Truncated Diffusion Probabilistic Models
Huangjie Zheng, Pengcheng He, Weizhu Chen, Mingyuan Zhou
arXiv 2022. [Paper]
19 Feb 2022
Understanding DDPM Latent Codes Through Optimal Transport
Valentin Khrulkov, Ivan Oseledets
arXiv 2022. [Paper]
14 Feb 2022
Learning Fast Samplers for Diffusion Models by Differentiating Through Sample Quality
Daniel Watson, William Chan, Jonathan Ho, Mohammad Norouzi
ICLR 2022. [Paper]
11 Feb 2022
Progressive Distillation for Fast Sampling of Diffusion Models
Tim Salimans, Jonathan Ho
ICLR 2022. [Paper]
1 Feb 2022
Analytic-DPM: an Analytic Estimate of the Optimal Reverse Variance in Diffusion Probabilistic Models
Fan Bao, Chongxuan Li, Jun Zhu, Bo Zhang
arXiv 2022. [Paper]
17 Jan 2022
DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents
Kushagra Pandey, Avideep Mukherjee, Piyush Rai, Abhishek Kumar
arXiv 2022. [Paper] [Github]
2 Jan 2022
Itô-Taylor Sampling Scheme for Denoising Diffusion Probabilistic Models using Ideal Derivatives
Hideyuki Tachibana, Mocho Go, Muneyoshi Inahara, Yotaro Katayama, Yotaro Watanabe
arXiv 2021. [Paper]
26 Dec 2021
GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models
Alex Nichol1, Prafulla Dhariwal1, Aditya Ramesh1, Pranav Shyam, Pamela Mishkin, Bob McGrew, Ilya Sutskever, Mark Chen
arXiv 2021. [Paper]
20 Dec 2021
High-Resolution Image Synthesis with Latent Diffusion Models
Robin Rombach1, Andreas Blattmann1, Dominik Lorenz, Patrick Esser, Björn Ommer
arXiv 2021. [Paper] [Github]
20 Dec 2021
Heavy-tailed denoising score matching
Jacob Deasy, Nikola Simidjievski, Pietro Liò
arXiv 2021. [Paper]
17 Dec 2021
High Fidelity Visualization of What Your Self-Supervised Representation Knows About
Florian Bordes, Randall Balestriero, Pascal Vincent
arXiv 2021. [Paper]
16 Dec 2021
Tackling the Generative Learning Trilemma with Denoising Diffusion GANs
Zhisheng Xiao, Karsten Kreis, Arash Vahdat
arXiv 2021. [Paper] [Project]
15 Dec 2021
Score-Based Generative Modeling with Critically-Damped Langevin Diffusion
Tim Dockhorn, Arash Vahdat, Karsten Kreis
arXiv 2021. [Paper] [Project]
14 Dec 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
arXiv 2021. [Paper]
10 Dec 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
arXiv 2021. [Paper]
3 Dec 2021
Diffusion Autoencoders: Toward a Meaningful and Decodable Representation
Konpat Preechakul, Nattanat Chatthee, Suttisak Wizadwongsa, Supasorn Suwajanakorn
arXiv 2021. [Paper] [Project]
30 Dec 2021
Conditional Image Generation with Score-Based Diffusion Models
Georgios Batzolis, Jan Stanczuk, Carola-Bibiane Schönlieb, Christian Etmann
arXiv 2021. [Paper]
26 Nov 2021
Unleashing Transformers: Parallel Token Prediction with Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized Codes
Sam Bond-Taylor1, Peter Hessey1, Hiroshi Sasaki, Toby P. Breckon, Chris G. Willcocks
arXiv 2021. [Paper] [Github]
24 Nov 2021
Diffusion Normalizing Flow
Qinsheng Zhang, Yongxin Chen
NeurIPS 2021. [Paper] [Github]
14 Oct 2021
Denoising Diffusion Gamma Models
Eliya Nachmani1, Robin San Roman1, Lior Wolf
arXiv 2021. [Paper]
10 Oct 2021
Score-based Generative Neural Networks for Large-Scale Optimal Transport
Max Daniels, Tyler Maunu, Paul Hand
arXiv 2021. [Paper]
7 Oct 2021
Score-Based Generative Classifiers
Roland S. Zimmermann, Lukas Schott, Yang Song, Benjamin A. Dunn, David A. Klindt
arXiv 2021. [Paper]
1 Oct 2021
Classifier-Free Diffusion Guidance
Jonathan Ho, Tim Salimans
NeurIPS Workshop 2021. [Paper]
28 Sep 2021
Bilateral Denoising Diffusion Models
Max W. Y. Lam, Jun Wang, Rongjie Huang, Dan Su, Dong Yu
arXiv 2021. [Paper] [Project]
26 Aug 2021
ImageBART: Bidirectional Context with Multinomial Diffusion for Autoregressive Image Synthesis
Patrick Esser1, Robin Rombach1, Andreas Blattmann1, Björn Ommer
NeurIPS 2021. [Paper] [Project]
19 Aug 2021
ILVR: Conditioning Method for Denoising Diffusion Probabilistic Models
Jooyoung Choi, Sungwon Kim, Yonghyun Jeong, Youngjune Gwon, Sungroh Yoon
ICCV 2021 (Oral). [Paper] [Github]
6 Aug 2021
SDEdit: Image Synthesis and Editing with Stochastic Differential Equations
Chenlin Meng, Yang Song, Jiaming Song, Jiajun Wu, Jun-Yan Zhu, Stefano Ermon
arXiv 2021. [Paper] [Project] [Github]
2 Aug 2021
Structured Denoising Diffusion Models in Discrete State-Spaces
Jacob Austin1, Daniel D. Johnson1, Jonathan Ho, Daniel Tarlow, Rianne van den Berg
arXiv 2021. [Paper]
7 Jul 2021
Variational Diffusion Models
Diederik P. Kingma1, Tim Salimans1, Ben Poole, Jonathan Ho
arXiv 2021. [Paper] [Github]
1 Jul 2021
Deep Generative Learning via Schrödinger Bridge
Gefei Wang, Yuling Jiao, Qian Xu, Yang Wang, Can Yang
ICML 2021. [Paper]
19 Jun 2021
Non Gaussian Denoising Diffusion Models
Eliya Nachmani1, Robin San Roman1, Lior Wolf
arXiv 2021. [Paper] [Project]
14 Jun 2021
D2C: Diffusion-Denoising Models for Few-shot Conditional Generation
Abhishek Sinha1, Jiaming Song1, Chenlin Meng, Stefano Ermon
arXiv 2021. [Paper] [Project] [Github]
12 Jun 2021
Score-based Generative Modeling in Latent Space
Arash Vahdat1, Karsten Kreis1, Jan Kautz
arXiv 2021. [Paper]
10 Jun 2021
Learning to Efficiently Sample from Diffusion Probabilistic Models
Daniel Watson, Jonathan Ho, Mohammad Norouzi, William Chan
arXiv 2021. [Paper]
7 Jun 2021
A Variational Perspective on Diffusion-Based Generative Models and Score Matching
Chin-Wei Huang, Jae Hyun Lim, Aaron Courville
ICML Workshop 2021. [Paper] [Github]
5 Jun 2021
Diffusion Schrödinger Bridge with Applications to Score-Based Generative Modeling
Valentin De Bortoli, James Thornton, Jeremy Heng, Arnaud Doucet
arXiv 2021. [Paper] [Project] [Github]
1 Jun 2021
On Fast Sampling of Diffusion Probabilistic Models
Zhifeng Kong, Wei Ping
ICML Workshop 2021. [Paper] [Github]
31 May 2021
Cascaded Diffusion Models for High Fidelity Image Generation
Jonathan Ho1, Chitwan Saharia1, William Chan, David J. Fleet, Mohammad Norouzi, Tim Salimans
arXiv 2021. [Paper] [Project]
30 May 2021
Gotta Go Fast When Generating Data with Score-Based Models
Alexia Jolicoeur-Martineau, Ke Li, Rémi Piché-Taillefer, Tal Kachman, Ioannis Mitliagkas
arXiv 2021. [Paper] [Github]
28 May 2021
Diffusion Models Beat GANs on Image Synthesis
Prafulla Dhariwal1, Alex Nichol1
arXiv 2021. [Paper] [Github]
11 May 2021
Image Super-Resolution via Iterative Refinement
Chitwan Saharia, Jonathan Ho, William Chan, Tim Salimans, David J. Fleet, Mohammad Norouzi
arXiv 2021. [Paper] [Project] [Github]
15 Apr 2021
Noise Estimation for Generative Diffusion Models
Robin San-Roman1, Eliya Nachmani1, Lior Wolf
arXiv 2021. [Paper]
6 Apr 2021
Improved Denoising Diffusion Probabilistic Models
Alex Nichol1, Prafulla Dhariwal1
ICLR 2021. [Paper] [Github]
18 Feb 2021
Maximum Likelihood Training of Score-Based Diffusion Models
Yang Song1, Conor Durkan1, Iain Murray, Stefano Ermon
arXiv 2021. [Paper]
22 Jan 2021
Learning Energy-Based Models by Diffusion Recovery Likelihood
Ruiqi Gao, Yang Song, Ben Poole, Ying Nian Wu, Diederik P. Kingma
ICLR 2021. [Paper] [Github]
15 Dec 2020
Score-Based Generative Modeling through Stochastic Differential Equations
Yang Song, Jascha Sohl-Dickstein, Diederik P. Kingma, Abhishek Kumar, Stefano Ermon, Ben Poole
ICLR 2021 (Oral). [Paper] [Github]
26 Nov 2020
Variational (Gradient) Estimate of the Score Function in Energy-based Latent Variable Models
Fan Bao, Kun Xu, Chongxuan Li, Lanqing Hong, Jun Zhu, Bo Zhang
ICML 2021. [Paper]
16 Oct 2020
Denoising Diffusion Implicit Models
Jiaming Song, Chenlin Meng, Stefano Ermon
ICLR 2021. [Paper] [Github]
6 Oct 2020
Adversarial score matching and improved sampling for image generation
Alexia Jolicoeur-Martineau1, Rémi Piché-Taillefer1, Rémi Tachet des Combes, Ioannis Mitliagkas
ICLR 2021. [Paper] [Github]
11 Sep 2020
Denoising Diffusion Probabilistic Models
Jonathan Ho, Ajay Jain, Pieter Abbeel
NeurIPS 2020. [Paper] [Github] [Github2]
19 Jun 2020
Improved Techniques for Training Score-Based Generative Models
Yang Song, Stefano Ermon
NeurIPS 2020. [Paper] [Github]
16 Jun 2020
Generative Modeling by Estimating Gradients of the Data Distribution
Yang Song, Stefano Ermon
NeurIPS 2019. [Paper] [Project] [Github]
12 Jul 2019
Neural Stochastic Differential Equations: Deep Latent Gaussian Models in the Diffusion Limit
Belinda Tzen, Maxim Raginsky
arXiv 2019. [Paper]
23 May 2019
Deep Unsupervised Learning using Nonequilibrium Thermodynamics
Jascha Sohl-Dickstein, Eric A. Weiss, Niru Maheswaranathan, Surya Ganguli
ICML 2015. [Paper] [Github]
2 Mar 2015
Diffusion models as plug-and-play priors
Alexandros Graikos, Nikolay Malkin, Nebojsa Jojic, Dimitris Samaras
arXiv 2022. [Paper]
17 June 2022
Diffusion Models for Implicit Image Segmentation Ensembles
Julia Wolleb1, Robin Sandkühler1, Florentin Bieder, Philippe Valmaggia, Philippe C. Cattin
arXiv 2021. [Paper]
6 Dec 2021
Label-Efficient Semantic Segmentation with Diffusion Models
Dmitry Baranchuk, Ivan Rubachev, Andrey Voynov, Valentin Khrulkov, Artem Babenko
arXiv 2021. [Paper] [Github]
6 Dec 2021
SegDiff: Image Segmentation with Diffusion Probabilistic Models
Tomer Amit, Eliya Nachmani, Tal Shaharbany, Lior Wolf
arXiv 2021. [Paper]
1 Dec 2021
Discrete Contrastive Diffusion for Cross-Modal and Conditional Generation
Ye Zhu, Yu Wu, Kyle Olszewski, Jian Ren, Sergey Tulyakov, Yan Yan
arXiv 2022. [Paper] [Github]
15 Jun 2022
SAR Despeckling using a Denoising Diffusion Probabilistic Model
Malsha V. Perera, Nithin Gopalakrishnan Nair, Wele Gedara Chaminda Bandara, Vishal M. Patel
arXiv 2022. [Paper]
9 Jun 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
arXiv 2022. [Paper] [Project] [Github]
25 May 2022
VQBB: Image-to-image Translation with Vector Quantized Brownian Bridge
Bo Li, Kaitao Xue, Bin Liu, Yu-Kun Lai
arXiv 2022. [Paper]
16 May 2022
The Swiss Army Knife for Image-to-Image Translation: Multi-Task Diffusion Models
Julia Wolleb1, Robin Sandkühler1, Florentin Bieder, Philippe C. Cattin
arXiv 2022. [Paper]
6 Apr 2022
Dual Diffusion Implicit Bridges for Image-to-Image Translation
Xuan Su, Jiaming Song, Chenlin Meng, Stefano Ermon
arXiv 2022. [Paper]
16 Mar 2022
Denoising Diffusion Restoration Models
Bahjat Kawar, Michael Elad, Stefano Ermon, Jiaming Song
arXiv 2022. [Paper]
27 Jan 2022
DiffuseMorph: Unsupervised Deformable Image Registration Along Continuous Trajectory Using Diffusion Models
Boah Kim, Inhwa Han, Jong Chul Ye
arXiv 2021. [Paper]
9 Dec 2021
Diffusion Autoencoders: Toward a Meaningful and Decodable Representation
Konpat Preechakul, Nattanat Chatthee, Suttisak Wizadwongsa, Supasorn Suwajanakorn
arXiv 2021. [Paper] [Project]
30 Dec 2021
Conditional Image Generation with Score-Based Diffusion Models
Georgios Batzolis, Jan Stanczuk, Carola-Bibiane Schönlieb, Christian Etmann
arXiv 2021. [Paper]
26 Nov 2021
ILVR: Conditioning Method for Denoising Diffusion Probabilistic Models
Jooyoung Choi, Sungwon Kim, Yonghyun Jeong, Youngjune Gwon, Sungroh Yoon
ICCV 2021 (Oral). [Paper] [Github]
6 Aug 2021
UNIT-DDPM: UNpaired Image Translation with Denoising Diffusion Probabilistic Models
Hiroshi Sasaki, Chris G. Willcocks, Toby P. Breckon
arXiv 2021. [Paper]
12 Apr 2021
Denoising Diffusion Restoration Models
Bahjat Kawar, Michael Elad, Stefano Ermon, Jiaming Song
arXiv 2022. [Paper]
27 Jan 2022
DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents
Kushagra Pandey, Avideep Mukherjee, Piyush Rai, Abhishek Kumar
arXiv 2022. [Paper] [Github]
2 Jan 2022
High-Resolution Image Synthesis with Latent Diffusion Models
Robin Rombach1, Andreas Blattmann1, Dominik Lorenz, Patrick Esser, Björn Ommer
arXiv 2021. [Paper] [Github]
20 Dec 2021
Come-Closer-Diffuse-Faster: Accelerating Conditional Diffusion Models for Inverse Problems through Stochastic Contraction
Hyungjin Chung, Byeongsu Sim, Jong Chul Ye
arXiv 2021. [Paper]
9 Dec 2021
Conditional Image Generation with Score-Based Diffusion Models
Georgios Batzolis, Jan Stanczuk, Carola-Bibiane Schönlieb, Christian Etmann
arXiv 2021. [Paper]
26 Nov 2021
S3RP: Self-Supervised Super-Resolution and Prediction for Advection-Diffusion Process
Chulin Wang, Kyongmin Yeo, Xiao Jin, Andres Codas, Levente J. Klein, Bruce Elmegreen
arXiv 2021. [Paper]
8 Nov 2021
Autoregressive Diffusion Models
Emiel Hoogeboom, Alexey A. Gritsenko, Jasmijn Bastings, Ben Poole, Rianne van den Berg, Tim Salimans
arXiv 2021. [Paper]
5 Oct 2021
ILVR: Conditioning Method for Denoising Diffusion Probabilistic Models
Jooyoung Choi, Sungwon Kim, Yonghyun Jeong, Youngjune Gwon, Sungroh Yoon
ICCV 2021 (Oral). [Paper] [Github]
6 Aug 2021
Cascaded Diffusion Models for High Fidelity Image Generation
Jonathan Ho1, Chitwan Saharia1, William Chan, David J. Fleet, Mohammad Norouzi, Tim Salimans
arXiv 2021. [Paper] [Project]
30 May 2021
SRDiff: Single Image Super-Resolution with Diffusion Probabilistic Models
Haoying Li, Yifan Yang, Meng Chang, Huajun Feng, Zhihai Xu, Qi Li, Yueting Chen
arXiv 2021. [Paper]
30 Apr 2021
Image Super-Resolution via Iterative Refinement
Chitwan Saharia, Jonathan Ho, William Chan, Tim Salimans, David J. Fleet, Mohammad Norouzi
arXiv 2021. [Paper] [Project] [Github]
15 Apr 2021
Blended Latent Diffusion
Omri Avrahami, Ohad Fried, Dani Lischinski
ACM 2022. [Paper] [Project] [Github]
6 Jun 2022
Improving Diffusion Models for Inverse Problems using Manifold Constraints
Hyungjin Chung1, Byeongsu Sim1, Dohoon Ryu, Jong Chul Ye
arXiv 2022. [Paper]
2 Jun 2022
DiVAE: Photorealistic Images Synthesis with Denoising Diffusion Decoder
Jie Shi1, Chenfei Wu1, Jian Liang, Xiang Liu, Nan Duan
arXiv 2022. [Paper]
1 Jun 2022
Denoising Diffusion Restoration Models
Bahjat Kawar, Michael Elad, Stefano Ermon, Jiaming Song
arXiv 2022. [Paper]
27 Jan 2022
RePaint: Inpainting using Denoising Diffusion Probabilistic Models
Andreas Lugmayr, Martin Danelljan, Andres Romero, Fisher Yu, Radu Timofte, Luc Van Gool
arXiv 2022. [Paper] [Github]
24 Jan 2022
High-Resolution Image Synthesis with Latent Diffusion Models
Robin Rombach1, Andreas Blattmann1, Dominik Lorenz, Patrick Esser, Björn Ommer
arXiv 2021. [Paper] [Github]
20 Dec 2021
Tackling the Generative Learning Trilemma with Denoising Diffusion GANs
Zhisheng Xiao, Karsten Kreis, Arash Vahdat
arXiv 2021. [Paper] [Project]
15 Dec 2021
Come-Closer-Diffuse-Faster: Accelerating Conditional Diffusion Models for Inverse Problems through Stochastic Contraction
Hyungjin Chung, Byeongsu Sim, Jong Chul Ye
arXiv 2021. [Paper]
9 Dec 2021
Conditional Image Generation with Score-Based Diffusion Models
Georgios Batzolis, Jan Stanczuk, Carola-Bibiane Schönlieb, Christian Etmann
arXiv 2021. [Paper]
26 Nov 2021
Unleashing Transformers: Parallel Token Prediction with Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized Codes
Sam Bond-Taylor1, Peter Hessey1, Hiroshi Sasaki, Toby P. Breckon, Chris G. Willcocks
arXiv 2021. [Paper] [Github]
24 Nov 2021
ILVR: Conditioning Method for Denoising Diffusion Probabilistic Models
Jooyoung Choi, Sungwon Kim, Yonghyun Jeong, Youngjune Gwon, Sungroh Yoon
ICCV 2021 (Oral). [Paper] [Github]
6 Aug 2021
SDEdit: Image Synthesis and Editing with Stochastic Differential Equations
Chenlin Meng, Yang Song, Jiaming Song, Jiajun Wu, Jun-Yan Zhu, Stefano Ermon
arXiv 2021. [Paper] [Project] [Github]
2 Aug 2021
Discrete Contrastive Diffusion for Cross-Modal and Conditional Generation
Ye Zhu, Yu Wu, Kyle Olszewski, Jian Ren, Sergey Tulyakov, Yan Yan
arXiv 2022. [Paper] [Github]
15 Jun 2022
Blended Latent Diffusion
Omri Avrahami, Ohad Fried, Dani Lischinski
ACM 2022. [Paper] [Project] [Github]
6 Jun 2022
Compositional Visual Generation with Composable Diffusion Models
Nan Liu1, Shuang Li1, Yilun Du1, Antonio Torralba, Joshua B. Tenenbaum
arXiv 2022. [Paper] [Project]
3 Jun 2022
DiVAE: Photorealistic Images Synthesis with Denoising Diffusion Decoder
Jie Shi1, Chenfei Wu1, Jian Liang, Xiang Liu, Nan Duan
arXiv 2022. [Paper]
1 Jun 2022
Improved Vector Quantized Diffusion Models
Zhicong Tang, Shuyang Gu, Jianmin Bao, Dong Chen, Fang Wen
arXiv 2022. [Paper] [Github]
31 May 2022
Text2Human: Text-Driven Controllable Human Image Generation
Yuming Jiang, Shuai Yang, Haonan Qiu, Wayne Wu, Chen Change Loy, Ziwei Liu
ACM 2022. [Paper]
31 May 2022
Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding
Chitwan Saharia1, William Chan1, 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
arXiv 2022. [Paper]
23 May 2022
Retrieval-Augmented Diffusion Models
Andreas Blattmann1, Robin Rombach1, Kaan Oktay, Björn Ommer
arXiv 2022. [Paper]
25 Apr 2022
Hierarchical Text-Conditional Image Generation with CLIP Latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, Mark Chen
arXiv 2022. [Paper]
13 Apr 2022
KNN-Diffusion: Image Generation via Large-Scale Retrieval
Oron Ashual, Shelly Sheynin, Adam Polyak, Uriel Singer, Oran Gafni, Eliya Nachmani, Yaniv Taigman
arXiv 2022. [Paper]
6 Apr 2022
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
arXiv 2021. [Paper]
10 Dec 2021
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
CVPR 2022. [Paper] [Github]
29 Nov 2021
Blended Diffusion for Text-driven Editing of Natural Images
Omri Avrahami, Dani Lischinski, Ohad Fried
CVPR 2022. [Paper] [Project] [Github]
29 Nov 2021
DiffusionCLIP: Text-guided Image Manipulation Using Diffusion Models
Gwanghyun Kim, Jong Chul Ye
CVPR 2022. [Paper]
6 Oct 2021