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Collecting annotated data for semantic segmentation is time-consuming and hard to scale up.
Semantic contours from inverse detectors
Bharath Hariharan, Pablo Arbelaez, Lubomir D. Bourdev, Subhransu Maji, and Jitendra Malik · 2011
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Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
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Discriminative unsupervised feature learning with exemplar convolutional neural networks
Alexey Dosovitskiy, Philipp Fischer, Jost Tobias Springenberg, Martin Riedmiller, and Thomas Brox · 2015
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Mark Everingham, S. M. Ali Eslami, Luc Van Gool, Christopher K. I. Williams, John M. Winn, and Andrew Zisserman · 2015
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Imagenet large scale visual recognition challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, et al · 2015
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The cityscapes dataset for semantic urban scene understanding
Marius Cordts, Mohamed Omran, Sebastian Ramos, Timo Rehfeld, Markus Enzweiler, Rodrigo Benenson, Uwe Franke, Stefan Roth, and Bernt Schiele · 2016
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Deep residual learning for image recognition
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Sgdr: Stochastic gradient descent with warm restarts
Ilya Loshchilov and Frank Hutter · 2016
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mixup: Beyond empirical risk minimization
Hongyi Zhang, Moustapha Cisse, Yann N Dauphin, and David Lopez-Paz · 2017
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Coco-stuff: Thing and stuff classes in context
Holger Caesar, Jasper Uijlings, and Vittorio Ferrari · 2018
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Encoder-decoder with atrous separable convolution for semantic image segmentation
Liang-Chieh Chen, Yukun Zhu, George Papandreou, Florian Schroff, and Hartwig Adam · 2018
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Learning deep representations by mutual information estimation and maximization
R Devon Hjelm, Alex Fedorov, Samuel Lavoie-Marchildon, Karan Grewal, Phil Bachman, Adam Trischler, and Yoshua Bengio · 2018
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Dynamic-structured semantic propagation network
Xiaodan Liang, Eric Xing, and Hongfei Zhou · 2018
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Representation learning with contrastive predictive coding
Aaron van den Oord, Yazhe Li, and Oriol Vinyals · 2018
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Unsupervised feature learning via non-parametric instance discrimination
Zhirong Wu, Yuanjun Xiong, Stella X Yu, and Dahua Lin · 2018
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Yonglong Tian, Dilip Krishnan, and Phillip Isola · 2019
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Momentum contrast for unsupervised visual representation learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick · 2020
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Supervised contrastive learning
Prannay Khosla, Piotr Teterwak, Chen Wang, Aaron Sarna, Yonglong Tian, Phillip Isola, Aaron Maschinot, Ce Liu, and Dilip Krishnan · 2020
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Mseg: A composite dataset for multi-domain semantic segmentation
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Zhenda Xie, Yutong Lin, Zheng Zhang, Yue Cao, Stephen Lin, and Han Hu · 2020
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Object detection with a unified label space from multiple datasets
Xiangyun Zhao, Samuel Schulter, Gaurav Sharma, Yi-Hsuan Tsai, Manmohan Chandraker, and Ying Wu · 2020
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Unsupervised learning of visual features by contrasting cluster assignments
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Bootstrap your own latent: A new approach to self-supervised learning
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Contrastive learning for label-efficient semantic segmentation
Xiangyun Zhao, Raviteja Vemulapalli, Philip Andrew Mansfield, Boqing Gong, Bradley Green, Lior Shapira, and Ying Wu · 2020
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Inigo Alonso, Alberto Sabater, David Ferstl, Luis Montesano, and Ana C. Murillo · 2021
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Unsupervised semantic segmentation by contrasting object mask proposals
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Exploring cross-image pixel contrast for semantic segmentation
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Simple multi-dataset detection
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