Deconstructing Denoising Diffusion Models for Self-Supervised Learning

25 January 2024

Papers citing "Deconstructing Denoising Diffusion Models for Self-Supervised Learning"

47 / 47 papers shown

Title
Conjuring Positive Pairs for Efficient Unification of Representation Learning and Image Synthesis Imanol G. Estepa Jesús M. Rodríguez-de-Vera Ignacio Sarasúa Bhalaji Nagarajan Petia Radeva 163 0 0 19 Mar 2025
USP: Unified Self-Supervised Pretraining for Image Generation and Understanding Xiangxiang Chu Renda Li Yong Wang 225 1 0 08 Mar 2025
Learning Actionable World Models for Industrial Process Control Peng Yan Ahmed Abdulkadir Gerrit A. Schatte Giulia Anguzzi Joonsu Gha Nikola Pascher Matthias Rosenthal Yunlong Gao Benjamin Grewe Thilo Stadelmann DRL AI4CE 102 0 0 03 Mar 2025
From Pixels to Components: Eigenvector Masking for Visual Representation Learning Alice Bizeul Thomas M. Sutter Alain Ryser Bernhard Schölkopf Julius von Kügelgen Julia E. Vogt 172 2 0 10 Feb 2025
Understanding Representation Dynamics of Diffusion Models via Low-Dimensional Modeling Xiao Li Zekai Zhang Xiang Li Siyi Chen Zhihui Zhu Peng Wang Qing Qu DiffM 169 1 0 09 Feb 2025
BiGR: Harnessing Binary Latent Codes for Image Generation and Improved Visual Representation Capabilities Shaozhe Hao Xuantong Liu Xianbiao Qi Shihao Zhao Bojia Zi Rong Xiao Kai Han Kwan-Yee K. Wong 160 3 0 18 Oct 2024
UniGEM: A Unified Approach to Generation and Property Prediction for Molecules Shikun Feng Yuyan Ni Yan Lu Zhi-Ming Ma Wei-Ying Ma Yanyan Lan 88 7 0 14 Oct 2024
Representation Alignment for Generation: Training Diffusion Transformers Is Easier Than You Think Sihyun Yu Sangkyung Kwak Huiwon Jang Jongheon Jeong Jonathan Huang Jinwoo Shin Saining Xie OCL 153 98 0 09 Oct 2024
Zero-Shot Video Restoration and Enhancement Using Pre-Trained Image Diffusion Model Cong Cao Huanjing Yue Xin Liu Jingyu Yang DiffM VGen 113 1 0 02 Jul 2024
SODA: Bottleneck Diffusion Models for Representation Learning Drew A. Hudson Daniel Zoran Mateusz Malinowski Andrew Kyle Lampinen Andrew Jaegle James L. McClelland Loic Matthey Felix Hill Alexander Lerchner DiffM 83 55 0 29 Nov 2023
Diffusion Models Beat GANs on Image Classification Soumik Mukhopadhyay M. Gwilliam Vatsal Agarwal Namitha Padmanabhan A. Swaminathan Srinidhi Hegde Dinesh Manocha Abhinav Shrivastava DiffM 134 48 1 17 Jul 2023
Diffusion Models as Masked Autoencoders Chen Wei K. Mangalam Po-Yao (Bernie) Huang Yanghao Li Haoqi Fan Hu Xu Huiyu Wang Cihang Xie Alan Yuille Christoph Feichtenhofer DiffM SyDa 76 53 0 06 Apr 2023
Mixed Autoencoder for Self-supervised Visual Representation Learning Kai Chen Zhili Liu Lanqing Hong Hang Xu Zhenguo Li Dit-Yan Yeung SSL 100 45 0 30 Mar 2023
Denoising Diffusion Autoencoders are Unified Self-supervised Learners Weilai Xiang Hongyu Yang Di Huang Yunhong Wang DiffM 106 78 0 17 Mar 2023
Scalable Diffusion Models with Transformers William S. Peebles Saining Xie GNN 103 2,386 0 19 Dec 2022
Exploring Plain Vision Transformer Backbones for Object Detection Yanghao Li Hanzi Mao Ross B. Girshick Kaiming He ViT 90 814 0 30 Mar 2022
Corrupted Image Modeling for Self-Supervised Visual Pre-Training Yuxin Fang Li Dong Hangbo Bao Xinggang Wang Furu Wei 69 88 0 07 Feb 2022
High-Resolution Image Synthesis with Latent Diffusion Models Robin Rombach A. Blattmann Dominik Lorenz Patrick Esser Bjorn Ommer 3DV 474 15,734 0 20 Dec 2021
SimMIM: A Simple Framework for Masked Image Modeling Zhenda Xie Zheng Zhang Yue Cao Yutong Lin Jianmin Bao Zhuliang Yao Qi Dai Han Hu 202 1,360 0 18 Nov 2021
Masked Autoencoders Are Scalable Vision Learners Kaiming He Xinlei Chen Saining Xie Yanghao Li Piotr Dollár Ross B. Girshick ViT TPM 467 7,814 0 11 Nov 2021
Diffusion Models Beat GANs on Image Synthesis Prafulla Dhariwal Alex Nichol 250 7,933 0 11 May 2021
An Empirical Study of Training Self-Supervised Vision Transformers Xinlei Chen Saining Xie Kaiming He ViT 157 1,868 0 05 Apr 2021
Improved Denoising Diffusion Probabilistic Models Alex Nichol Prafulla Dhariwal DiffM 352 3,715 0 18 Feb 2021
Taming Transformers for High-Resolution Image Synthesis Patrick Esser Robin Rombach Bjorn Ommer ViT 131 2,984 0 17 Dec 2020
Score-Based Generative Modeling through Stochastic Differential Equations Yang Song Jascha Narain Sohl-Dickstein Diederik P. Kingma Abhishek Kumar Stefano Ermon Ben Poole DiffM SyDa 350 6,551 0 26 Nov 2020
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale Alexey Dosovitskiy Lucas Beyer Alexander Kolesnikov Dirk Weissenborn Xiaohua Zhai ... Matthias Minderer G. Heigold Sylvain Gelly Jakob Uszkoreit N. Houlsby ViT 667 41,369 0 22 Oct 2020
Denoising Diffusion Probabilistic Models Jonathan Ho Ajay Jain Pieter Abbeel DiffM 672 18,276 0 19 Jun 2020
Decision-Making with Auto-Encoding Variational Bayes Romain Lopez Pierre Boyeau Nir Yosef Michael I. Jordan Jeffrey Regier BDL 476 10,591 0 17 Feb 2020
A Simple Framework for Contrastive Learning of Visual Representations Ting-Li Chen Simon Kornblith Mohammad Norouzi Geoffrey E. Hinton SSL 375 18,859 0 13 Feb 2020
Momentum Contrast for Unsupervised Visual Representation Learning Kaiming He Haoqi Fan Yuxin Wu Saining Xie Ross B. Girshick SSL 210 12,121 0 13 Nov 2019
RandAugment: Practical automated data augmentation with a reduced search space E. D. Cubuk Barret Zoph Jonathon Shlens Quoc V. Le MQ 241 3,503 0 30 Sep 2019
Generative Modeling by Estimating Gradients of the Data Distribution Yang Song Stefano Ermon SyDa DiffM 258 3,954 0 12 Jul 2019
Large Scale Adversarial Representation Learning Jeff Donahue Karen Simonyan SSL 130 543 0 04 Jul 2019
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features Sangdoo Yun Dongyoon Han Seong Joon Oh Sanghyuk Chun Junsuk Choe Y. Yoo OOD 622 4,798 0 13 May 2019
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Jacob Devlin Ming-Wei Chang Kenton Lee Kristina Toutanova VLM SSL SSeg 1.8K 95,114 0 11 Oct 2018
The Unreasonable Effectiveness of Deep Features as a Perceptual Metric Richard Y. Zhang Phillip Isola Alexei A. Efros Eli Shechtman Oliver Wang EGVM 379 11,877 0 11 Jan 2018
Neural Discrete Representation Learning Aaron van den Oord Oriol Vinyals Koray Kavukcuoglu BDL SSL OCL 228 5,061 0 02 Nov 2017
mixup: Beyond Empirical Risk Minimization Hongyi Zhang Moustapha Cissé Yann N. Dauphin David Lopez-Paz NoLa 282 9,797 0 25 Oct 2017
Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour Priya Goyal Piotr Dollár Ross B. Girshick P. Noordhuis Lukasz Wesolowski Aapo Kyrola Andrew Tulloch Yangqing Jia Kaiming He 3DH 128 3,685 0 08 Jun 2017
Layer Normalization Jimmy Lei Ba J. Kiros Geoffrey E. Hinton 420 10,526 0 21 Jul 2016
Asynchrony begets Momentum, with an Application to Deep Learning Jeff Donahue Philipp Krahenbuhl Stefan Hadjis Christopher Ré 92 142 0 31 May 2016
Context Encoders: Feature Learning by Inpainting Deepak Pathak Philipp Krahenbuhl Jeff Donahue Trevor Darrell Alexei A. Efros SSL 69 5,299 0 25 Apr 2016
Deep Networks with Stochastic Depth Gao Huang Yu Sun Zhuang Liu Daniel Sedra Kilian Q. Weinberger 215 2,361 0 30 Mar 2016
Deep Unsupervised Learning using Nonequilibrium Thermodynamics Jascha Narain Sohl-Dickstein Eric A. Weiss Niru Maheswaranathan Surya Ganguli SyDa DiffM 306 7,005 0 12 Mar 2015
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift Sergey Ioffe Christian Szegedy OOD 463 43,328 0 11 Feb 2015
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 1.7K 100,479 0 04 Sep 2014
Microsoft COCO: Common Objects in Context Nayeon Lee Michael Maire Serge J. Belongie Lubomir Bourdev Ross B. Girshick James Hays Pietro Perona Deva Ramanan C. L. Zitnick Piotr Dollár ObjD 424 43,777 0 01 May 2014