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Despite the recent visually-pleasing results achieved, the massive computational cost has been a long-standing flaw for diffusion probabilistic models (DPMs), which, in turn, greatly limits their applications on resource-limited platforms.
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U-net: Convolutional networks for biomedical image segmentation
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
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Tero Karras, Timo Aila, Samuli Laine, and Jaakko Lehtinen · 2017
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Focal loss for dense object detection
Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He, and Piotr Dollár · 2017
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Ilya Loshchilov and Frank Hutter · 2017
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Attention is all you need
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Squeeze-and-excitation networks
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Cbam: Convolutional block attention module
Sanghyun Woo, Jongchan Park, Joon-Young Lee, and In So Kweon · 2018
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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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Ccnet: Criss-cross attention for semantic segmentation
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Structured knowledge distillation for semantic segmentation
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Generative modeling by estimating gradients of the data distribution
Yang Song and Stefano Ermon · 2019
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Frequency principle: Fourier analysis sheds light on deep neural networks
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Training behavior of deep neural network in frequency domain
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Frequency bias in neural networks for input of non-uniform density
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Score-based generative modeling through stochastic differential equations
Yang Song, Jascha Sohl-Dickstein, Diederik P Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole · 2021
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Score-based generative modeling in latent space
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Deep long-tailed learning: A survey
Yifan Zhang, Bingyi Kang, Bryan Hooi, Shuicheng Yan, and Jiashi Feng · 2021
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Analytic-dpm: an analytic estimate of the optimal reverse variance in diffusion probabilistic models
Fan Bao, Chongxuan Li, Jun Zhu, and Bo Zhang · 2022
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Perception prioritized training of diffusion models
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Joel Frank, Thorsten Eisenhofer, Lea Schönherr, Asja Fischer, Dorothea Kolossa, and Thorsten Holz · 2020
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Generative adversarial networks
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Decoupling representation and classifier for long-tailed recognition
Bingyi Kang, Saining Xie, Marcus Rohrbach, Zhicheng Yan, Albert Gordo, Jiashi Feng, and Yannis Kalantidis · 2020
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Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2020
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Sliced score matching: A scalable approach to density and score estimation
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Ssd-gan: Measuring the realness in the spatial and spectral domains
Yuanqi Chen, Ge Li, Cece Jin, Shan Liu, and Thomas Li · 2021
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Vector quantized diffusion model for text-to-image synthesis
Shuyang Gu, Dong Chen, Jianmin Bao, Fang Wen, Bo Zhang, Dongdong Chen, Lu Yuan, and Baining Guo · 2022
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Imagen video: High definition video generation with diffusion models
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Progressive distillation for fast sampling of diffusion models
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Wavegan: Frequency-aware gan for high-fidelity few-shot image generation
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