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Conservative-Progressive Collaborative Learning for Semi-supervised
  Semantic Segmentation

Conservative-Progressive Collaborative Learning for Semi-supervised Semantic Segmentation

30 November 2022
Siqi Fan
F. Zhu
Zunlei Feng
Yisheng Lv
Min-Gyoo Song
Fei-Yue Wang
ArXivPDFHTML

Papers citing "Conservative-Progressive Collaborative Learning for Semi-supervised Semantic Segmentation"

3 / 3 papers shown
Title
RESMatch: Referring Expression Segmentation in a Semi-Supervised Manner
RESMatch: Referring Expression Segmentation in a Semi-Supervised Manner
Ying-Dong Zang
Chenglong Fu
Runlong Cao
Didi Zhu
Min Zhang
Wenjun Hu
Lanyun Zhu
Tianrun Chen
32
6
0
08 Feb 2024
In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label
  Selection Framework for Semi-Supervised Learning
In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning
Mamshad Nayeem Rizve
Kevin Duarte
Y. S. Rawat
M. Shah
217
508
0
15 Jan 2021
There Are Many Consistent Explanations of Unlabeled Data: Why You Should
  Average
There Are Many Consistent Explanations of Unlabeled Data: Why You Should Average
Ben Athiwaratkun
Marc Finzi
Pavel Izmailov
A. Wilson
199
243
0
14 Jun 2018
1