Fetching the paper…
Reading the bibliography…
Recent advances in semi-supervised learning (SSL) demonstrate that a combination of consistency regularization and pseudo-labeling can effectively improve image classification accuracy in the low-data regime.
Resnest: Split-attention networks
Hang Zhang, Chongruo Wu, Zhongyue Zhang, Yi Zhu, Zhi Zhang, Haibin Lin, Yue Sun, Tong He, Jonas Muller, R. Manmatha, Mu Li, and Alexander Smola · 2004
Earlier work this paper cites.
Semi-supervised learning by entropy minimization
Yves Grandvalet and Yoshua Bengio · 2005
Earlier work this paper cites.
A simple semi-supervised learning framework for object detection
Kihyuk Sohn, Zizhao Zhang, Chun-Liang Li, Han Zhang, Chen-Yu Lee, and Tomas Pfister · 2005
Earlier work this paper cites.
Semantic contours from inverse detectors
Bharath Hariharan, Pablo Arbeláez, Lubomir Bourdev, Subhransu Maji, and Jitendra Malik · 2011
Earlier work this paper cites.
Efficient inference in fully connected crfs with gaussian edge potentials
Philipp Krähenbühl and Vladlen Koltun · 2011
Earlier work this paper cites.
Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks
Dong-Hyun Lee · 2013
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 C Lawrence Zitnick · 2014
Earlier work this paper cites.
Boxsup: Exploiting bounding boxes to supervise convolutional networks for semantic segmentation
Jifeng Dai, Kaiming He, and Jian Sun · 2015
Earlier work this paper cites.
The pascal visual object classes challenge: A retrospective
Mark Everingham, SM Ali Eslami, Luc Van Gool, Christopher KI Williams, John Winn, and Andrew Zisserman · 2015
Earlier work this paper cites.
Hypercolumns for object segmentation and fine-grained localization
Bharath Hariharan, Pablo Arbeláez, Ross Girshick, and Jitendra Malik · 2015
Earlier work this paper cites.
Spatial transformer networks
Max Jaderberg, Karen Simonyan, Andrew Zisserman, et al · 2015
Earlier work this paper cites.
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
Earlier work this paper cites.
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
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.
Temporal ensembling for semi-supervised learning
Samuli Laine and Timo Aila · 2016
Earlier work this paper cites.
Scribblesup: Scribble-supervised convolutional networks for semantic segmentation
Di Lin, Jifeng Dai, Jiaya Jia, Kaiming He, and Jian Sun · 2016
Earlier work this paper cites.
Regularization with stochastic transformations and perturbations for deep semi-supervised learning
Mehdi Sajjadi, Mehran Javanmardi, and Tolga Tasdizen · 2016
Earlier work this paper cites.
Learning deep features for discriminative localization
Bolei Zhou, Aditya Khosla, Agata Lapedriza, Aude Oliva, and Antonio Torralba · 2016
Earlier work this paper cites.
Xception: Deep learning with depthwise separable convolutions
François Chollet · 2017
Cited alongside, same era.
Improved regularization of convolutional neural networks with cutout
Terrance DeVries and Graham W Taylor · 2017
Cited alongside, same era.
On calibration of modern neural networks
Chuan Guo, Geoff Pleiss, Yu Sun, and Kilian Q Weinberger · 2017
Cited alongside, same era.
Exploiting saliency for object segmentation from image level labels
Seong Joon Oh, Rodrigo Benenson, Anna Khoreva, Zeynep Akata, Mario Fritz, and Bernt Schiele · 2017
Cited alongside, same era.
Grad-cam: Visual explanations from deep networks via gradient-based localization
Ramprasaath R Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, and Dhruv Batra · 2017
Cited alongside, same era.
Weakly supervised learning of instance segmentation with inter-pixel relations
Jiwoon Ahn, Sunghyun Cho, and Suha Kwak · 2019
Later among the works it cites.
Integral object mining via online attention accumulation
Peng-Tao Jiang, Qibin Hou, Yang Cao, Ming-Ming Cheng, Yunchao Wei, and Hong-Kai Xiong · 2019
Later among the works it cites.
Ficklenet: Weakly and semi-supervised semantic image segmentation using stochastic inference
Jungbeom Lee, Eunji Kim, Sungmin Lee, Jangho Lee, and Sungroh Yoon · 2019
Later among the works it cites.
Semi-supervised semantic segmentation with high-and low-level consistency
Sudhanshu Mittal, Maxim Tatarchenko, and Thomas Brox · 2019
Later among the works it cites.
Unsupervised data augmentation for consistency training
Qizhe Xie, Zihang Dai, Eduard Hovy, Minh-Thang Luong, and Quoc V. Le · 2019
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Nasim Souly, Concetto Spampinato, and Mubarak Shah · 2017
Cited alongside, same era.
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results
Antti Tarvainen and Harri Valpola · 2017
Cited alongside, same era.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
Cited alongside, same era.
Object region mining with adversarial erasing: A simple classification to semantic segmentation approach
Yunchao Wei, Jiashi Feng, Xiaodan Liang, Ming-Ming Cheng, Yao Zhao, and Shuicheng Yan · 2017
Cited alongside, same era.
Learning pixel-level semantic affinity with image-level supervision for weakly supervised semantic segmentation
Jiwoon Ahn and Suha Kwak · 2018
Cited alongside, same era.
Encoder-decoder with atrous separable convolution for semantic image segmentation
Liang-Chieh Chen, Yukun Zhu, George Papandreou, Florian Schroff, and Hartwig Adam · 2018
Cited alongside, same era.
Self-erasing network for integral object attention
Qibin Hou, PengTao Jiang, Yunchao Wei, and Ming-Ming Cheng · 2018
Cited alongside, same era.
Semi-supervised semantic segmentation needs strong, high-dimensional perturbations
Geoff French, Timo Aila, Samuli Laine, Michal Mackiewicz, and Graham Finlayson · 2020
Closest in time.
Guided collaborative training for pixel-wise semi-supervised learning
Zhanghan Ke, Di Qiu, Kaican Li, Qiong Yan, and Rynson WH Lau · 2020
Closest in time.
Structured consistency loss for semi-supervised semantic segmentation
Jongmok Kim, Jooyoung Jang, and Hyunwoo Park · 2020
Closest in time.
Pointrend: Image segmentation as rendering
Alexander Kirillov, Yuxin Wu, Kaiming He, and Ross Girshick · 2020
Closest in time.
Featmatch: Feature-based augmentation for semi-supervised learning
Chia-Wen Kuo, Chih-Yao Ma, Jia-Bin Huang, and Zsolt Kira · 2020
Closest in time.
Semi-supervised semantic segmentation via strong-weak dual-branch network
Wenfeng Luo and Meng Yang · 2020
Closest in time.
Semi-supervised semantic segmentation with cross-consistency training
Yassine Ouali, Céline Hudelot, and Myriam Tami · 2020
Closest in time.
Mining cross-image semantics for weakly supervised semantic segmentation
Guolei Sun, Wenguan Wang, Jifeng Dai, and Luc Van Gool · 2020
Closest in time.
Self-supervised equivariant attention mechanism for weakly supervised semantic segmentation
Yude Wang, Jie Zhang, Meina Kan, Shiguang Shan, and Xilin Chen · 2020
Closest in time.
Self-training with noisy student improves imagenet classification
Qizhe Xie, Minh-Thang Luong, Eduard Hovy, and Quoc V Le · 2020
Closest in time.
Improving semantic segmentation via self-training
Yi Zhu, Zhongyue Zhang, Chongruo Wu, Zhi Zhang, Tong He, Hang Zhang, R Manmatha, Mu Li, and Alexander Smola · 2020
Closest in time.
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
Closest in time.