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Being able to learn dense semantic representations of images without supervision is an important problem in computer vision.
Normalized cuts and image segmentation
Jianbo Shi and Jitendra Malik · 2000
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Contour detection and hierarchical image segmentation
Pablo Arbelaez, Michael Maire, Charless Fowlkes, and Jitendra Malik · 2010
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The pascal visual object classes (voc) challenge
Mark Everingham, Luc Van Gool, Christopher KI Williams, John Winn, and Andrew Zisserman · 2010
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Noise-contrastive estimation: A new estimation principle for unnormalized statistical models
Michael Gutmann and Aapo Hyvärinen · 2010
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Segmentation as selective search for object recognition
Koen EA Van de Sande, Jasper RR Uijlings, Theo Gevers, and Arnold WM Smeulders · 2011
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Saliency detection via absorbing markov chain
Bowen Jiang, Lihe Zhang, Huchuan Lu, Chuan Yang, and Ming-Hsuan Yang · 2013
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Saliency detection via dense and sparse reconstruction
Xiaohui Li, Huchuan Lu, Lihe Zhang, Xiang Ruan, and Ming-Hsuan Yang · 2013
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Hierarchical saliency detection
Q. Yan, L. Xu, J. Shi, and J. Jia · 2013
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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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Saliency optimization from robust background detection
Wangjiang Zhu, Shuang Liang, Yichen Wei, and Jian Sun · 2014
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Salient object detection: A benchmark
Ali Borji, Ming-Ming Cheng, Huaizu Jiang, and Jia Li · 2015
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Global contrast based salient region detection
Ming-Ming Cheng, Niloy J. Mitra, Xiaolei Huang, Philip H. S. Torr, and Shi-Min Hu · 2015
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Boxsup: Exploiting bounding boxes to supervise convolutional networks for semantic segmentation
Jifeng Dai, Kaiming He, and Jian Sun · 2015
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Unsupervised visual representation learning by context prediction
Carl Doersch, Abhinav Gupta, and Alexei A Efros · 2015
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Decoupled deep neural network for semi-supervised semantic segmentation
Seunghoon Hong, Hyeonwoo Noh, and Bohyung Han · 2015
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Learning visual groups from co-occurrences in space and time
Phillip Isola, Daniel Zoran, Dilip Krishnan, and Edward H Adelson · 2015
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Fully convolutional networks for semantic segmentation
Jonathan Long, Evan Shelhamer, and Trevor Darrell · 2015
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Weakly-and semi-supervised learning of a deep convolutional network for semantic image segmentation
George Papandreou, Liang-Chieh Chen, Kevin P Murphy, and Alan L Yuille · 2015
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Constrained convolutional neural networks for weakly supervised segmentation
Deepak Pathak, Philipp Krahenbuhl, and Trevor Darrell · 2015
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Learning to segment object candidates
Pedro OO Pinheiro, Ronan Collobert, and Piotr Dollár · 2015
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Holistically-nested edge detection
Saining Xie and Zhuowen Tu · 2015
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Learning to segment under various forms of weak supervision
Jia Xu, Alexander G Schwing, and Raquel Urtasun · 2015
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Multi-scale context aggregation by dilated convolutions
Fisher Yu and Vladlen Koltun · 2015
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Harf: Hierarchy-associated rich features for salient object detection
Wenbin Zou and Nikos Komodakis · 2015
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What’s the point: Semantic segmentation with point supervision
Amy Bearman, Olga Russakovsky, Vittorio Ferrari, and Li Fei-Fei · 2016
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What’s the point: Semantic segmentation with point supervision
Amy Bearman, Olga Russakovsky, Vittorio Ferrari, and Li Fei-Fei · 2016
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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
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Let there be color! joint end-to-end learning of global and local image priors for automatic image colorization with simultaneous classification
Satoshi Iizuka, Edgar Simo-Serra, and Hiroshi Ishikawa · 2016
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Scribblesup: Scribble-supervised convolutional networks for semantic segmentation
Di Lin, Jifeng Dai, Jiaya Jia, Kaiming He, and Jian Sun · 2016
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Unsupervised learning of visual representations by solving jigsaw puzzles
Mehdi Noroozi and Paolo Favaro · 2016
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Context encoders: Feature learning by inpainting
Deepak Pathak, Philipp Krahenbuhl, Jeff Donahue, Trevor Darrell, and Alexei A Efros · 2016
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A benchmark dataset and evaluation methodology for video object segmentation
F. Perazzi, J. Pont-Tuset, B. McWilliams, L. Van Gool, M. Gross, and A. Sorkine-Hornung · 2016
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Colorful image colorization
Richard Zhang, Phillip Isola, and Alexei A Efros · 2016
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Unsupervised learning by predicting noise
Piotr Bojanowski and Armand Joulin · 2017
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Rethinking atrous convolution for semantic image segmentation
Liang-Chieh Chen, George Papandreou, Florian Schroff, and Hartwig Adam · 2017
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Semantic instance segmentation with a discriminative loss function
Bert De Brabandere, Davy Neven, and Luc Van Gool · 2017
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Adversarial feature learning
Jeff Donahue, Philipp Krähenbühl, and Trevor Darrell · 2017
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Deeply supervised salient object detection with short connections
Qibin Hou, Ming-Ming Cheng, Xiaowei Hu, Ali Borji, Zhuowen Tu, and Philip HS Torr · 2017
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Panoptic segmentation
Alexander Kirillov, Kaiming He, Ross Girshick, Carsten Rother, and Piotr Dollár · 2019
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Deepusps: Deep robust unsupervised saliency prediction via self-supervision
Tam Nguyen, Maximilian Dax, Chaithanya Kumar Mummadi, Nhung Ngo, Thi Hoai Phuong Nguyen, Zhongyu Lou, and Thomas Brox · 2019
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Basnet: Boundary-aware salient object detection
Xuebin Qin, Zichen Zhang, Chenyang Huang, Chao Gao, Masood Dehghan, and Martin Jagersand · 2019
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Yonglong Tian, Dilip Krishnan, and Phillip Isola · 2019
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Salient object detection in the deep learning era: An in-depth survey
Wenguan Wang, Qiuxia Lai, Huazhu Fu, Jianbing Shen, Haibin Ling, and Ruigang Yang · 2019
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Anna Khoreva, Rodrigo Benenson, Jan Hendrik Hosang, Matthias Hein, and Bernt Schiele · 2017
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Colorization as a proxy task for visual understanding
Gustav Larsson, Michael Maire, and Gregory Shakhnarovich · 2017
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Non-local deep features for salient object detection
Zhiming Luo, Akshaya Mishra, Andrew Achkar, Justin Eichel, Shaozi Li, and Pierre-Marc Jodoin · 2017
Cited alongside, same era.
Representation learning by learning to count
Mehdi Noroozi, Hamed Pirsiavash, and Paolo Favaro · 2017
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Learning random-walk label propagation for weakly-supervised semantic segmentation
Paul Vernaza and Manmohan Chandraker · 2017
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Salient object detection: A discriminative regional feature integration approach
Jingdong Wang, Huaizu Jiang, Zejian Yuan, Ming-Ming Cheng, Xiaowei Hu, and Nanning Zheng · 2017
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Learning to detect salient objects with image-level supervision
Lijun Wang, Huchuan Lu, Yifan Wang, Mengyang Feng, Dong Wang, Baocai Yin, and Xiang Ruan · 2017
Cited alongside, same era.
Unsupervised moving object detection via contextual information separation
Yanchao Yang, Antonio Loquercio, Davide Scaramuzza, and Stefano Soatto · 2019
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Unsupervised embedding learning via invariant and spreading instance feature
Mang Ye, Xu Zhang, Pong C Yuen, and Shih-Fu Chang · 2019
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Self-supervised learning via conditional motion propagation
Xiaohang Zhan, Xingang Pan, Ziwei Liu, Dahua Lin, and Chen Change Loy · 2019
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Aet vs. aed: Unsupervised representation learning by auto-encoding transformations rather than data
Liheng Zhang, Guo-Jun Qi, Liqiang Wang, and Jiebo Luo · 2019
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Labelling unlabelled videos from scratch with multi-modal self-supervision
Yuki M Asano, Mandela Patrick, Christian Rupprecht, and Andrea Vedaldi · 2020
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Self-labelling via simultaneous clustering and representation learning
Yuki M. Asano, Christian Rupprecht, and Andrea Vedaldi · 2020
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Unsupervised learning of visual features by contrasting cluster assignments
Mathilde Caron, Ishan Misra, Julien Mairal, Priya Goyal, Piotr Bojanowski, and Armand Joulin · 2020
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Contrastive learning of global and local features for medical image segmentation with limited annotations
Krishna Chaitanya, Ertunc Erdil, Neerav Karani, and Ender Konukoglu · 2020
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A simple framework for contrastive learning of visual representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton · 2020
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Big self-supervised models are strong semi-supervised learners
Ting Chen, Simon Kornblith, Kevin Swersky, Mohammad Norouzi, and Geoffrey Hinton · 2020
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Improved baselines with momentum contrastive learning
Xinlei Chen, Haoqi Fan, Ross Girshick, and Kaiming He · 2020
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Bootstrap your own latent: A new approach to self-supervised learning
Jean-Bastien Grill, Florian Strub, Florent Altché, Corentin Tallec, Pierre H Richemond, Elena Buchatskaya, Carl Doersch, Bernardo Avila Pires, Zhaohan Daniel Guo, Mohammad Gheshlaghi Azar, et al · 2020
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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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Space-time correspondence as a contrastive random walk
Allan Jabri, Andrew Owens, and Alexei A. Efros · 2020
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Self-supervised visual feature learning with deep neural networks: A survey
Longlong Jing and Yingli Tian · 2020
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Prototypical contrastive learning of unsupervised representations
Junnan Li, Pan Zhou, Caiming Xiong, Richard Socher, and Steven CH Hoi · 2020
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Self-supervised learning of pretext-invariant representations
Ishan Misra and Laurens van der Maaten · 2020
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Autoregressive unsupervised image segmentation
Yassine Ouali, Céline Hudelot, and Myriam Tami · 2020
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Demystifying contrastive self-supervised learning: Invariances, augmentations and dataset biases
Senthil Purushwalkam and Abhinav Gupta · 2020
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Unsupervised object detection with lidar clues
Hao Tian, Yuntao Chen, Jifeng Dai, Zhaoxiang Zhang, and Xizhou Zhu · 2020
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What makes for good views for contrastive learning
Yonglong Tian, C. Sun, Ben Poole, Dilip Krishnan, C. Schmid, and Phillip Isola · 2020
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Scan: Learning to classify images without labels
Wouter Van Gansbeke, Simon Vandenhende, Stamatios Georgoulis, Marc Proesmans, and Luc Van Gool · 2020
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Understanding contrastive representation learning through alignment and uniformity on the hypersphere
Tongzhou Wang and Phillip Isola · 2020
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Clusterfit: Improving generalization of visual representations
Xueting Yan, Ishan Misra, Abhinav Gupta, Deepti Ghadiyaram, and Dhruv Mahajan · 2020
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Time-supervised primary object segmentation
Yanchao Yang, Brian Lai, and Stefano Soatto · 2020
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Uc-net: uncertainty inspired rgb-d saliency detection via conditional variational autoencoders
Jing Zhang, Deng-Ping Fan, Yuchao Dai, Saeed Anwar, Fatemeh Sadat Saleh, Tong Zhang, and Nick Barnes · 2020
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Self-supervised visual representation learning from hierarchical grouping
Xiao Zhang and Michael Maire · 2020
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Rethinking pre-training and self-training
Barret Zoph, Golnaz Ghiasi, Tsung-Yi Lin, Yin Cui, Hanxiao Liu, Ekin D Cubuk, and Quoc V Le · 2020
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