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To date, most existing self-supervised learning methods are designed and optimized for image classification.
Non-parametric local transforms for computing visual correspondence
Ramin Zabih and John Woodfill · 1994
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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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The PASCAL Visual Object Classes (VOC) Challenge
Mark Everingham, Luc Van Gool, Christopher KI Williams, John Winn, and Andrew Zisserman · 2010
Earlier work this paper cites.
StereoScan: Dense 3d reconstruction in real-time
Andreas Geiger, Julius Ziegler, and Christoph Stiller · 2011
Earlier work this paper cites.
Dense visual slam for rgb-d cameras
Christian Kerl, Jürgen Sturm, and Daniel Cremers · 2013
Earlier work this paper cites.
Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
Earlier work this paper cites.
Microsoft COCO: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and Lawrence Zitnick · 2014
Earlier work this paper cites.
Unsupervised visual representation learning by context prediction
Carl Doersch, Abhinav Gupta, and Alexei Efros · 2015
Earlier work this paper cites.
FlowNet: Learning optical flow with convolutional networks
Alexey Dosovitskiy, Philipp Fischer, Eddy Ilg, Philip Hausser, Caner Hazirbas, Vladimir Golkov, Patrick Van Der Smagt, Daniel Cremers, and Thomas Brox · 2015
Earlier work this paper cites.
Fully convolutional networks for semantic segmentation
Jonathan Long, Evan Shelhamer, and Trevor Darrell · 2015
Earlier work this paper cites.
Faster R-CNN: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2015
Earlier work this paper cites.
Universal correspondence network
Christopher Choy, JunYoung Gwak, Silvio Savarese, and Manmohan Chandraker · 2016
Earlier work this paper cites.
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
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
HyperNet: Towards accurate region proposal generation and joint object detection
Tao Kong, Anbang Yao, Yurong Chen, and Fuchun Sun · 2016
Earlier work this paper cites.
Unsupervised learning of visual representations by solving jigsaw puzzles
Mehdi Noroozi and Paolo Favaro · 2016
Earlier work this paper cites.
Context encoders: Feature learning by inpainting
Deepak Pathak, Philipp Krahenbuhl, Jeff Donahue, Trevor Darrell, and Alexei Efros · 2016
Earlier work this paper cites.
You Only Look Once: Unified, real-time object detection
Joseph Redmon, Santosh Divvala, Ross Girshick, and Ali Farhadi · 2016
Cited alongside, same era.
Structure-from-motion revisited
Johannes L Schonberger and Jan-Michael Frahm · 2016
Cited alongside, same era.
Unsupervised feature learning for dense correspondences across scenes
Chao Zhang, Chunhua Shen, and Tingzhi Shen · 2016
Cited alongside, same era.
Colorful image colorization
Richard Zhang, Phillip Isola, and Alexei Efros · 2016
Cited alongside, same era.
FCSS: Fully convolutional self-similarity for dense semantic correspondence
Seungryong Kim, Dongbo Min, Bumsub Ham, Sangryul Jeon, Stephen Lin, and Kwanghoon Sohn · 2017
Cited alongside, same era.
Feature pyramid networks for object detection
Tsung-Yi Lin, Piotr Dollár, Ross B. Girshick, Kaiming He, Bharath Hariharan, and Serge J. Belongie · 2017
Cited alongside, same era.
Yonglong Tian, Dilip Krishnan, and Phillip Isola · 2019
Later among the works it cites.
Detectron2
Yuxin Wu, Alexander Kirillov, Francisco Massa, Wan-Yen Lo, and Ross Girshick · 2019
Later among the works it cites.
Krishna Chaitanya, Ertunc Erdil, Neerav Karani, and Ender Konukoglu · 2020
Closest in time.
A simple framework for contrastive learning of visual representations
Ting Chen, Simon Kornblith, 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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YOLO9000: better, faster, stronger
Joseph Redmon and Ali Farhadi · 2017
Cited alongside, same era.
Unsupervised representation learning by predicting image rotations
Spyros Gidaris, Praveer Singh, and Nikos Komodakis · 2018
Cited alongside, same era.
DetNet: Design backbone for object detection
Zeming Li, Chao Peng, Gang Yu, Xiangyu Zhang, Yangdong Deng, and Jian Sun · 2018
Cited alongside, same era.
Exploring the limits of weakly supervised pretraining
Dhruv Mahajan, Ross Girshick, Vignesh Ramanathan, Kaiming He, Manohar Paluri, Yixuan Li, Ashwin Bharambe, and Laurens van der Maaten · 2018
Cited alongside, same era.
Representation learning with contrastive predictive coding
Aaron van den Oord, Yazhe Li, and Oriol Vinyals · 2018
Cited alongside, same era.
Unsupervised feature learning via non-parametric instance discrimination
Zhirong Wu, Yuanjun Xiong, Stella Yu, and Dahua Lin · 2018
Cited alongside, same era.
Jean-Bastien Grill, Florian Strub, Florent Altché, Corentin Tallec, Pierre Richemond, Elena Buchatskaya, Carl Doersch, Bernardo Avila Pires, Zhaohan Daniel Guo, Mohammad Gheshlaghi Azar, et al · 2020
Closest in time.
Self-supervised co-training for video representation learning
Tengda Han, Weidi Xie, and Andrew Zisserman · 2020
Closest in time.
Momentum contrast for unsupervised visual representation learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick · 2020
Closest in time.
mmsegmentation
OpenMMLab · 2020
Closest in time.
Unsupervised learning of dense visual representations
Pedro Pinheiro, Amjad Almahairi, Ryan Y Benmaleck, Florian Golemo, and Aaron Courville · 2020
Closest in time.
EfficientDet: Scalable and efficient object detection
Mingxing Tan, Ruoming Pang, and Quoc V Le · 2020
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What makes for good views for contrastive learning
Yonglong Tian, Chen Sun, Ben Poole, Dilip Krishnan, Cordelia Schmid, and Phillip Isola · 2020
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PointContrast: Unsupervised pre-training for 3d point cloud understanding
Saining Xie, Jiatao Gu, Demi Guo, Charles R Qi, Leonidas J Guibas, and Or Litany · 2020
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Online deep clustering for unsupervised representation learning
Xiaohang Zhan, Jiahao Xie, Ziwei Liu, Yew-Soon Ong, and Chen Change Loy · 2020
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Cheaper Pre-training Lunch: An efficient paradigm for object detection
Dongzhan Zhou, Xinchi Zhou, Hongwen Zhang, Shuai Yi, and Wanli Ouyang · 2020
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What makes instance discrimination good for transfer learning?
Nanxuan Zhao, Zhirong Wu, Rynson Lau, and Stephen Lin · 2021
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