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Contrastive visual pretraining based on the instance discrimination pretext task has made significant progress.
A simple framework for contrastive learning of visual representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton · 2002
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Improved baselines with momentum contrastive learning
Xinlei Chen, Haoqi Fan, Ross Girshick, and Kaiming He · 2003
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Guest editor’s introduction: special issue on inductive transfer learning
Daniel L Silver and Kristin P Bennett · 2008
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Ensemble of exemplar-svms for object detection and beyond
Tomasz Malisiewicz, Abhinav Gupta, and Alexei A Efros · 2011
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Diagnosing error in object detectors
Derek Hoiem, Yodsawalai Chodpathumwan, and Qieyun Dai · 2012
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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Overfeat: Integrated recognition, localization and detection using convolutional networks
Pierre Sermanet, David Eigen, Xiang Zhang, Michaël Mathieu, Rob Fergus, and Yann LeCun · 2013
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Lifelong machine learning systems: Beyond learning algorithms
Daniel L Silver, Qiang Yang, and Lianghao Li · 2013
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Analyzing the performance of multilayer neural networks for object recognition
Pulkit Agrawal, Ross Girshick, and Jitendra Malik · 2014
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Rich feature hierarchies for accurate object detection and semantic segmentation
Ross Girshick, Jeff Donahue, Trevor Darrell, and Jitendra Malik · 2014
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How transferable are features in deep neural networks?
Jason Yosinski, Jeff Clune, Yoshua Bengio, and Hod Lipson · 2014
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Facial landmark detection by deep multi-task learning
Zhanpeng Zhang, Ping Luo, Chen Change Loy, and Xiaoou Tang · 2014
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From generic to specific deep representations for visual recognition
Hossein Azizpour, Ali Sharif Razavian, Josephine Sullivan, Atsuto Maki, and Stefan Carlsson · 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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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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Texture synthesis using convolutional neural networks
Leon Gatys, Alexander S Ecker, and Matthias Bethge · 2015
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Deep convolutional neural fields for depth estimation from a single image
Fayao Liu, Chunhua Shen, and Guosheng Lin · 2015
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Fully convolutional networks for semantic segmentation
Jonathan Long, Evan Shelhamer, and Trevor Darrell · 2015
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Faster r-cnn: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2015
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Image style transfer using convolutional neural networks
Leon A Gatys, Alexander S Ecker, and Matthias Bethge · 2016
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What makes imagenet good for transfer learning?
Minyoung Huh, Pulkit Agrawal, and Alexei A Efros · 2016
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The synthia dataset: A large collection of synthetic images for semantic segmentation of urban scenes
German Ros, Laura Sellart, Joanna Materzynska, David Vazquez, and Antonio M Lopez · 2016
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Matching networks for one shot learning
Oriol Vinyals, Charles Blundell, Timothy Lillicrap, Daan Wierstra, et al · 2016
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Colorful image colorization
Unsupervised pre-training of image features on non-curated data
Mathilde Caron, Piotr Bojanowski, Julien Mairal, and Armand Joulin · 2019
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A closer look at few-shot classification
Wei-Yu Chen, Yen-Cheng Liu, Zsolt Kira, Yu-Chiang Wang, and Jia-Bin Huang · 2019
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Representation similarity analysis for efficient task taxonomy & transfer learning
Kshitij Dwivedi and Gemma Roig · 2019
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Scaling and benchmarking self-supervised visual representation learning
Priya Goyal, Dhruv Mahajan, Abhinav Gupta, and Ishan Misra · 2019
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Rethinking imagenet pre-training
Kaiming He, Ross Girshick, and Piotr Dollár · 2019
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Data-efficient image recognition with contrastive predictive coding
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Richard Zhang, Phillip Isola, and Alexei A Efros · 2016
Cited alongside, same era.
Rethinking atrous convolution for semantic image segmentation
Liang-Chieh Chen, George Papandreou, Florian Schroff, and Hartwig Adam · 2017
Cited alongside, same era.
Multi-task self-supervised visual learning
Carl Doersch and Andrew Zisserman · 2017
Cited alongside, same era.
Mask r-cnn
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick · 2017
Cited alongside, same era.
Hide-and-seek: Forcing a network to be meticulous for weakly-supervised object and action localization
Krishna Kumar Singh and Yong Jae Lee · 2017
Cited alongside, same era.
Unsupervised representation learning by predicting image rotations
Spyros Gidaris, Praveer Singh, and Nikos Komodakis · 2018
Cited alongside, same era.
Large-scale celebfaces attributes (celeba) dataset
Ziwei Liu, Ping Luo, Xiaogang Wang, and Xiaoou Tang · 2018
Cited alongside, same era.
Olivier J Hénaff, Aravind Srinivas, Jeffrey De Fauw, Ali Razavi, Carl Doersch, SM Eslami, and Aaron van den Oord · 2019
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Revisiting self-supervised visual representation learning
Alexander Kolesnikov, Xiaohua Zhai, and Lucas Beyer · 2019
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Do better imagenet models transfer better?
Simon Kornblith, Jonathon Shlens, and Quoc V Le · 2019
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Which tasks should be learned together in multi-task learning?
Trevor Standley, Amir R Zamir, Dawn Chen, Leonidas Guibas, Jitendra Malik, and Silvio Savarese · 2019
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Yonglong Tian, Dilip Krishnan, and Phillip Isola · 2019
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Transferability and hardness of supervised classification tasks
Anh T Tran, Cuong V Nguyen, and Tal Hassner · 2019
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Branched multi-task networks: deciding what layers to share
Simon Vandenhende, Stamatios Georgoulis, Bert De Brabandere, and Luc Van Gool · 2019
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Characterizing and avoiding negative transfer
Zirui Wang, Zihang Dai, Barnabás Póczos, and Jaime Carbonell · 2019
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Local aggregation for unsupervised learning of visual embeddings
Chengxu Zhuang, Alex Lin Zhai, and Daniel Yamins · 2019
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Learning representations by predicting bags of visual words
Spyros Gidaris, Andrei Bursuc, Nikos Komodakis, Patrick Pérez, and Matthieu Cord · 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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Self-supervised learning of pretext-invariant representations
Ishan Misra and Laurens van der Maaten · 2020
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Distilling localization for self-supervised representation learning
Nanxuan Zhao, Zhirong Wu, Rynson WH Lau, and Stephen Lin · 2020
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