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Semantic segmentation labels are expensive and time consuming to acquire.
Probability of error of some adaptive pattern-recognition machines
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Xinlei Chen, Haoqi Fan, Ross Girshick, and Kaiming He · 2003
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Pascal Vincent · 2011
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Generative adversarial nets
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Carl Doersch, Abhinav Gupta, and Alexei A. Efros · 2015
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Diederik P Kingma and Jimmy Ba · 2015
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Deep unsupervised learning using nonequilibrium thermodynamics
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Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich · 2015
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The cityscapes dataset for semantic urban scene understanding
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Context encoders: Feature learning by inpainting
Deepak Pathak, Philipp Krähenbühl, Jeff Donahue, Trevor Darrell, and Alexei A. Efros · 2016
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Colorful image colorization
Richard Zhang, Phillip Isola, and Alexei A. Efros · 2016
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Improved regularization of convolutional neural networks with cutout
Terrance DeVries and Graham W Taylor · 2017
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Semi supervised semantic segmentation using generative adversarial network
Nasim Souly, Concetto Spampinato, and Mubarak Shah · 2017
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Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results
Antti Tarvainen and Harri Valpola · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Split-brain autoencoders: Unsupervised learning by cross-channel prediction
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Deep clustering for unsupervised learning of visual features
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Wei-Chih Hung, Yi-Hsuan Tsai, Yan-Ting Liou, Yen-Yu Lin, and Ming-Hsuan Yang · 2018
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Unsupervised learning of dense visual representations
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A survey on semi-supervised learning
Jesper E Van Engelen and Holger H Hoos · 2020
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Rethinking semantic segmentation from a sequence-to-sequence perspective with Transformers
Sixiao Zheng, Jiachen Lu, Hengshuang Zhao, Xiatian Zhu, Zekun Luo, Yabiao Wang, Yanwei Fu, Jianfeng Feng, Tao Xiang, Philip H.S. Torr, and Li Zhang · 2020
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Improving semantic segmentation via self-training
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Aaron van den Oord, Yazhe Li, and Oriol Vinyals · 2018
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Tal Remez, Jonathan Huang, and Matthew Brown · 2018
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Bolei Zhou, Hang Zhao, Xavier Puig, Sanja Fidler, Adela Barriuso, and Antonio Torralba · 2018
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Object discovery with a copy-pasting gan
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Label-efficient semantic segmentation with diffusion models
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Diffusion models beat gans on image synthesis
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Peco: Perceptual codebook for bert pre-training of vision transformers
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Simple copy-paste is a strong data augmentation method for instance segmentation
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Masked autoencoders are scalable vision learners
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Cascaded diffusion models for high fidelity image generation
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Argmax flows and multinomial diffusion: Towards non-autoregressive language models
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Srdiff: Single image super-resolution with diffusion probabilistic models
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Swin transformer: Hierarchical vision transformer using shifted windows
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Semi-supervised semantic segmentation with high-and low-level consistency
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Improved denoising diffusion probabilistic models
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Learning transferable visual models from natural language supervision
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Score-based generative modeling through stochastic differential equations
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Segmenter: Transformer for semantic segmentation
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Pixel contrastive-consistent semi-supervised semantic segmentation
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ibot: Image bert pre-training with online tokenizer
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PseudoSeg: Designing pseudo labels for semantic segmentation
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Context autoencoder for self-supervised representation learning
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