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Score-based diffusion models have captured widespread attention and funded fast progress of recent vision generative tasks.
The Caltech-UCSD Birds-200-2011 Dataset
Catherine Wah, Steve Branson, Peter Welinder, Pietro Perona, and Serge Belongie · 2011
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Auto-Encoding Variational Bayes
Diederik P. Kingma and Max Welling · 2014
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Deep Learning Face Attributes in the Wild
Ziwei Liu, Ping Luo, Xiaogang Wang, and Xiaoou Tang · 2015
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Fully Convolutional Networks for Semantic Segmentation
Jonathan Long, Evan Shelhamer, and Trevor Darrell · 2015
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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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LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop
Fisher Yu, Ari Seff, Yinda Zhang, Shuran Song, Thomas Funkhouser, and Jianxiong Xiao · 2015
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Deep Residual Learning for Image Recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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GANs Trained by a Two Time-Scale Update Rule Converge to a Nash Equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, Günter Klambauer, and Sepp Hochreiter · 2017
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Decoupled Weight Decay Regularization
Ilya Loshchilov and Frank Hutter · 2017
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PixelCNN++: Improving the PixelCNN with Discretized Logistic Mixture Likelihood and Other Modifications
Tim Salimans, Andrej Karpathy, Xi Chen, and Diederik P. Kingma · 2017
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Large Scale GAN Training for High Fidelity Natural Image Synthesis
Andrew Brock, Jeff Donahue, and Karen Simonyan · 2018
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Group Normalization
Yuxin Wu and Kaiming He · 2018
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Generative Modeling by Estimating Gradients of the Data Distribution
Yang Song and Stefano Ermon · 2019
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End-to-End Object Detection with Transformers
Nicolas Carion, Francisco Massa, Gabriel Synnaeve, Nicolas Usunier, Alexander Kirillov, and Sergey Zagoruyko · 2020
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Effectively Unbiased FID and Inception Score and where to find them
Min Jin Chong and David Forsyth · 2020
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Denoising Diffusion Probabilistic Models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Training Generative Adversarial Networks with Limited Data
Tero Karras, Miika Aittala, Janne Hellsten, Samuli Laine, Jaakko Lehtinen, and Timo Aila · 2020
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Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, Peter J Liu, et al · 2020
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Improved Techniques for Training Score-Based Generative Models
Yang Song and Stefano Ermon · 2020
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Conceptual 12M: Pushing Web-Scale Image-Text Pre-Training To Recognize Long-Tail Visual Concepts
Soravit Changpinyo, Piyush Sharma, Nan Ding, and Radu Soricut · 2021
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CoAtNet: Marrying Convolution and Attention for All Data Sizes
Zihang Dai, Hanxiao Liu, Quoc V Le, and Mingxing Tan · 2021
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Diffusion Models Beat GANs on Image Synthesis
Prafulla Dhariwal and Alexander Nichol · 2021
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An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, and Neil Houlsby · 2021
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ConViT: Improving Vision Transformers with Soft Convolutional Inductive Biases
Stéphane d’Ascoli, Hugo Touvron, Matthew L Leavitt, Ari S Morcos, Giulio Biroli, and Levent Sagun · 2021
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Multiscale Vision Transformers
Haoqi Fan, Bo Xiong, Karttikeya Mangalam, Yanghao Li, Zhicheng Yan, Jitendra Malik, and Christoph Feichtenhofer · 2021
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Improve Vision Transformers Training by Suppressing Over-smoothing
Chengyue Gong, Dilin Wang, Meng Li, Vikas Chandra, and Qiang Liu · 2021
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TransGAN: Two Pure Transformers Can Make One Strong GAN, and That Can Scale Up
Yifan Jiang, Shiyu Chang, and Zhangyang Wang · 2021
Cited alongside, same era.
ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision
Wonjae Kim, Bokyung Son, and Ildoo Kim · 2021
Cited alongside, same era.
Perception Prioritized Training of Diffusion Models
Jooyoung Choi, Jungbeom Lee, Chaehun Shin, Sungwon Kim, Hyunwoo Kim, and Sungroh Yoon · 2022
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An Empirical Study of Training End-to-End Vision-and-Language Transformers
Zi-Yi Dou, Yichong Xu, Zhe Gan, Jianfeng Wang, Shuohang Wang, Lijuan Wang, Chenguang Zhu, Pengchuan Zhang, Lu Yuan, Nanyun Peng, et al · 2022
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Masked Autoencoders Are Scalable Vision Learners
Kaiming He, Xinlei Chen, Saining Xie, Yanghao Li, Piotr Dollár, and Ross Girshick · 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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Classifier-free Diffusion Guidance
Jonathan Ho and Tim Salimans · 2022
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ViTGAN: Training GANs with Vision Transformers
Kwonjoon Lee, Huiwen Chang, Lu Jiang, Han Zhang, Zhuowen Tu, and Ce Liu · 2021
Cited alongside, same era.
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, and Baining Guo · 2021
Cited alongside, same era.
SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations
Chenlin Meng, Yutong He, Yang Song, Jiaming Song, Jiajun Wu, Jun-Yan Zhu, and Stefano Ermon · 2021
Cited alongside, same era.
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, and Mark Chen · 2021
Cited alongside, same era.
Improved Denoising Diffusion Probabilistic Models
Alexander Quinn Nichol and Prafulla Dhariwal · 2021
Cited alongside, same era.
Learning Transferable Visual Models From Natural Language Supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
Cited alongside, same era.
Denoising Diffusion Implicit Models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2021
Cited alongside, same era.
Soft Truncation: A Universal Training Technique of Score-based Diffusion Model for High Precision Score Estimation
Dongjun Kim, Seungjae Shin, Kyungwoo Song, Wanmo Kang, and Il-Chul Moon · 2022
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DN-DETR: Accelerate DETR Training by Introducing Query DeNoising
Feng Li, Hao Zhang, Shilong Liu, Jian Guo, Lionel M Ni, and Lei Zhang · 2022
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Swinv2-Imagen: Hierarchical Vision Transformer Diffusion Models for Text-to-Image Generation
Ruijun Li, Weihua Li, Yi Yang, Hanyu Wei, Jianhua Jiang, and Quan Bai · 2022
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DAB-DETR: Dynamic Anchor Boxes are Better Queries for DETR
Shilong Liu, Feng Li, Hao Zhang, Xiao Yang, Xianbiao Qi, Hang Su, Jun Zhu, and Lei Zhang · 2022
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On Distillation of Guided Diffusion Models
Chenlin Meng, Ruiqi Gao, Diederik P Kingma, Stefano Ermon, Jonathan Ho, and Tim Salimans · 2022
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Scalable Diffusion Models with Transformers
William Peebles and Saining Xie · 2022
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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
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Palette: Image-to-Image Diffusion Models
Chitwan Saharia, William Chan, Huiwen Chang, Chris Lee, Jonathan Ho, Tim Salimans, David Fleet, and Mohammad Norouzi · 2022
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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, et al · 2022
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Image Super-Resolution via Iterative Refinement
Chitwan Saharia, Jonathan Ho, William Chan, Tim Salimans, David J Fleet, and Mohammad Norouzi · 2022
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Progressive Distillation for Fast Sampling of Diffusion Models
Tim Salimans and Jonathan Ho · 2022
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LAION-5B: An open large-scale dataset for training next generation image-text models
Christoph Schuhmann, Romain Beaumont, Richard Vencu, Cade Gordon, Ross Wightman, Mehdi Cherti, Theo Coombes, Aarush Katta, Clayton Mullis, Mitchell Wortsman, et al · 2022
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Tackling the generative learning trilemma with denoising diffusion GANs
Zhisheng Xiao, Karsten Kreis, and Arash Vahdat · 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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DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection
Hao Zhang, Feng Li, Shilong Liu, Lei Zhang, Hang Su, Jun Zhu, Lionel M Ni, and Heung-Yeung Shum · 2022
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Nested Hierarchical Transformer: Towards Accurate, Data-Efficient and Interpretable Visual Understanding
Zizhao Zhang, Han Zhang, Long Zhao, Ting Chen, Sercan Ö Arik, and Tomas Pfister · 2022
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