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Diffusion-based models have shown the merits of generating high-quality visual data while preserving better diversity in recent studies.
Adversarial score matching and improved sampling for image generation
Alexia Jolicoeur-Martineau, Remi Piche-Taillefer, Rémi Tachet des Combes, and Ioannis Mitliagkas · 2009
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Caltech-ucsd birds 200
Peter Welinder, Steve Branson, Takeshi Mita, Catherine Wah, Florian Schroff, Serge Belongie, and Pietro Perona · 2010
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Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Sohl-Dickstein, Eric A. Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
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Learning deep representation for imbalanced classification
Chen Huang, Yining Li, Chen Change Loy, and Xiaoou Tang · 2016
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Factors in finetuning deep model for object detection with long-tail distribution
Wanli Ouyang, Xiaogang Wang, Cong Zhang, and Xiaokang Yang · 2016
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Improved techniques for training gans
Tim Salimans, Ian Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, Xi Chen, and Xi Chen · 2016
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
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Webvision database: Visual learning and understanding from web data
Wen Li, Limin Wang, Wei Li, Eirikur Agustsson, and Luc Van Gool · 2017
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Stabilizing training of generative adversarial networks through regularization
Kevin Roth, Aurelien Lucchi, Sebastian Nowozin, and Thomas Hofmann · 2017
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Neural discrete representation learning
Aaron van den Oord, Oriol Vinyals, and Koray Kavukcuoglu · 2017
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Generative modeling using the sliced Wasserstein distance
Ishan Deshpande, Ziyu Zhang, and Alexander G Schwing · 2018
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The inaturalist species classification and detection dataset
Grant Van Horn, Oisin Mac Aodha, Yang Song, Yin Cui, Chen Sun, Alexander Shepard, Hartwig Adam, Pietro Perona, and Serge J. Belongie · 2018
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Exploring the limits of weakly supervised pretraining
Dhruv Mahajan, Ross Girshick, Vignesh Ramanathan, Kaiming He, Manohar Paluri, Yixuan Li, Ashwin Bharambe, and Laurens van der Maaten · 2018
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Spectral normalization for generative adversarial networks
Takeru Miyato, Toshiki Kataoka, Masanori Koyama, and Yuichi Yoshida · 2018
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Assessing generative models via precision and recall
Mehdi S. M. Sajjadi, Olivier Bachem, Mario Lucic, Olivier Bousquet, and Sylvain Gelly · 2018
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Large scale GAN training for high fidelity natural image synthesis
Andrew Brock, Jeff Donahue, and Karen Simonyan · 2019
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Learning imbalanced datasets with label-distribution-aware margin loss
Kaidi Cao, Colin Wei, Adrien Gaidon, Nikos Arechiga, and Tengyu Ma · 2019
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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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Large-scale long-tailed recognition in an open world
Ziwei Liu, Zhongqi Miao, Xiaohang Zhan, Jiayun Wang, Boqing Gong, and Stella X. Yu · 2019
Cited alongside, same era.
Feature transfer learning for face recognition with under-represented data
Xi Yin, Xiang Yu, Kihyuk Sohn, Xiaoming Liu, and Manmohan Chandraker · 2019
Cited alongside, same era.
Feature space augmentation for long-tailed data
Peng Chu, Xiao Bian, Shaopeng Liu, and Haibin Ling · 2020
Cited alongside, same era.
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, et al · 2020
Cited alongside, same era.
Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
Cited alongside, same era.
Class balancing gan with a classifier in the loop
Harsh Rangwani, Konda Reddy Mopuri, and R. Venkatesh Babu · 2021
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Denoising diffusion implicit models, 2021
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2021
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Regularizing generative adversarial networks under limited data
Hung-Yu Tseng, Lu Jiang, Ce Liu, Ming-Hsuan Yang, and Weilong Yang · 2021
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Rsg: A simple but effective module for learning imbalanced datasets
Jianfeng Wang, Thomas Lukasiewicz, Xiaolin Hu, Jianfei Cai, and Zhenghua Xu · 2021
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Classifier-free diffusion guidance
Jonathan Ho and Tim Salimans · 2022
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Tero Karras, Miika Aittala, Janne Hellsten, Samuli Laine, Jaakko Lehtinen, and Timo Aila · 2020
Cited alongside, same era.
M2m: Imbalanced classification via major-to-minor translation
Jaehyung Kim, Jongheon Jeong, and Jinwoo Shin · 2020
Cited alongside, same era.
Deep representation learning on long-tailed data: A learnable embedding augmentation perspective
Jialun Liu, Yifan Sun, Chuchu Han, Zhaopeng Dou, and Wenhui Li · 2020
Cited alongside, same era.
Differentiable augmentation for data-efficient gan training
Shengyu Zhao, Zhijian Liu, Ji Lin, Jun-Yan Zhu, and Song Han · 2020
Cited alongside, same era.
Score-based generative modeling in latent space
Jan Kautz Arash Vahdat, Karsten Kreis · 2021
Cited alongside, same era.
Exploring simple siamese representation learning
Xinlei Chen and Kaiming He · 2021
Cited alongside, same era.
Diffusion models beat GANs on image synthesis
Prafulla Dhariwal and Alexander Quinn Nichol · 2021
Cited alongside, same era.
Jonathan Ho, Tim Salimans, Alexey Gritsenko, William Chan, Mohammad Norouzi, and David J Fleet · 2022
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Long-tailed classification of thorax diseases on chest x-ray: A new benchmark study
Greg Holste, Song Wang, Ziyu Jiang, Thomas C. Shen, George L. Shih, Ronald M. Summers, Yifan Peng, and Zhangyang Wang · 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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Self-supervised dense consistency regularization for image-to-image translation
Minsu Ko, Eunju Cha, Sungjoo Suh, Huijin Lee, Jae-Joon Han, Jinwoo Shin, and Bohyung Han · 2022
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MRI reconstruction via data driven markov chain with joint uncertainty estimation
Guanxiong Luo, Martin Heide, and Martin Uecker · 2022
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Guided diffusion model for adversarial purification from random noise
Yuntian Gu Quanlin Wu, Hang Ye · 2022
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Improving gans for long-tailed data through group spectral regularization
Harsh Rangwani, Naman Jaswani, Tejan Karmali, Varun Jampani, and R. Venkatesh Babu · 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 A. Lee, Jonathan Ho, Tim Salimans, David J. Fleet, and Mohammad Norouzi · 2022
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Generating high fidelity data from low-density regions using diffusion models
Vikash Sehwag, Caner Hazirbas, Albert Gordo, Firat Ozgenel, and Cristian Canton · 2022
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Solving inverse problems in medical imaging with score-based generative models
Yang Song, Liyue Shen, Lei Xing, and Stefano Ermon · 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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