Semi-supervised semantic segmentation needs strong, varied perturbations

5 June 2019

Papers citing "Semi-supervised semantic segmentation needs strong, varied perturbations"

24 / 24 papers shown

Title
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features Sangdoo Yun Dongyoon Han Seong Joon Oh Sanghyuk Chun Junsuk Choe Y. Yoo OOD 604 4,766 0 13 May 2019
MixMatch: A Holistic Approach to Semi-Supervised Learning David Berthelot Nicholas Carlini Ian Goodfellow Nicolas Papernot Avital Oliver Colin Raffel 137 3,022 0 06 May 2019
Interpolation Consistency Training for Semi-Supervised Learning Vikas Verma Kenji Kawaguchi Alex Lamb Arno Solin Arno Solin Yoshua Bengio David Lopez-Paz 101 769 0 09 Mar 2019
S4-Net: Geometry-Consistent Semi-Supervised Semantic Segmentation Sinisa Stekovic Friedrich Fraundorfer Vincent Lepetit 53 4 0 27 Dec 2018
Universal Semi-Supervised Semantic Segmentation Tarun Kalluri G. Varma Manmohan Chandraker C. V. Jawahar 53 96 0 26 Nov 2018
Deep semi-supervised segmentation with weight-averaged consistency targets C. Perone Julien Cohen-Adad OOD 58 72 0 12 Jul 2018
There Are Many Consistent Explanations of Unlabeled Data: Why You Should Average Ben Athiwaratkun Marc Finzi Pavel Izmailov A. Wilson 243 244 0 14 Jun 2018
A DIRT-T Approach to Unsupervised Domain Adaptation Rui Shu Hung Bui Hirokazu Narui Stefano Ermon 72 621 0 23 Feb 2018
Adversarial Learning for Semi-Supervised Semantic Segmentation Wei-Chih Hung Yi-Hsuan Tsai Yan-Ting Liou Yen-Yu Lin Ming-Hsuan Yang GAN SSeg 104 552 0 22 Feb 2018
Smooth Neighbors on Teacher Graphs for Semi-supervised Learning Yucen Luo Jun Zhu Mengxi Li Yong Ren Bo Zhang 57 242 0 01 Nov 2017
mixup: Beyond Empirical Risk Minimization Hongyi Zhang Moustapha Cissé Yann N. Dauphin David Lopez-Paz NoLa 269 9,743 0 25 Oct 2017
Improved Regularization of Convolutional Neural Networks with Cutout Terrance Devries Graham W. Taylor 107 3,758 0 15 Aug 2017
Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning Takeru Miyato S. Maeda Masanori Koyama S. Ishii GAN 143 2,732 0 13 Apr 2017
Temporal Ensembling for Semi-Supervised Learning S. Laine Timo Aila UQCV 179 2,552 0 07 Oct 2016
Regularization With Stochastic Transformations and Perturbations for Deep Semi-Supervised Learning Mehdi S. M. Sajjadi Mehran Javanmardi Tolga Tasdizen BDL 77 1,112 0 14 Jun 2016
Mutual Exclusivity Loss for Semi-Supervised Deep Learning Mehdi S. M. Sajjadi Mehran Javanmardi Tolga Tasdizen SSL 35 80 0 09 Jun 2016
Fully Convolutional Networks for Semantic Segmentation Evan Shelhamer Jonathan Long Trevor Darrell VOS SSeg 542 37,806 0 20 May 2016
The Cityscapes Dataset for Semantic Urban Scene Understanding Marius Cordts Mohamed Omran Sebastian Ramos Timo Rehfeld Markus Enzweiler Rodrigo Benenson Uwe Franke Stefan Roth Bernt Schiele 921 11,587 0 06 Apr 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 1.9K 193,426 0 10 Dec 2015
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation Vijay Badrinarayanan Alex Kendall R. Cipolla SSeg 946 15,768 0 02 Nov 2015
U-Net: Convolutional Networks for Biomedical Image Segmentation Olaf Ronneberger Philipp Fischer Thomas Brox SSeg 3DV 1.5K 76,917 0 18 May 2015
Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs Liang-Chieh Chen George Papandreou Iasonas Kokkinos Kevin Patrick Murphy Alan Yuille SSeg 148 4,888 0 22 Dec 2014
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.4K 149,842 0 22 Dec 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 1.3K 100,213 0 04 Sep 2014