Semi-supervised semantic segmentation needs strong, varied perturbations

5 June 2019

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

9 / 9 papers shown

Title
What is the Added Value of UDA in the VFM Era? B. B. Englert Tommie Kerssies Gijs Dubbelman 44 0 0 25 Apr 2025
Boosting Semi-Supervised Semantic Segmentation with Probabilistic Representations Haoyu Xie Changqi Wang Mingkai Zheng Minjing Dong Shan You Chong Fu Chang Xu SSL 39 14 0 26 Oct 2022
Robust Mutual Learning for Semi-supervised Semantic Segmentation Pan Zhang Bo Zhang Ting Zhang Dong Chen Fang Wen 23 17 0 01 Jun 2021
All you need are a few pixels: semantic segmentation with PixelPick Gyungin Shin Weidi Xie Samuel Albanie VLM 21 42 0 13 Apr 2021
Contrastive Learning for Label-Efficient Semantic Segmentation Xiangyu Zhao Raviteja Vemulapalli Philip Mansfield Boqing Gong Bradley Green Lior Shapira Ying Nian Wu SSL SSeg 36 174 0 13 Dec 2020
Tilting at windmills: Data augmentation for deep pose estimation does not help with occlusions Rafal Pytel O. Kayhan J. C. V. Gemert 3DPC 24 6 0 20 Oct 2020
Semi-Supervised Semantic Segmentation with Cross-Consistency Training Yassine Ouali C´eline Hudelot Myriam Tami 28 709 0 19 Mar 2020
Parting with Illusions about Deep Active Learning Sudhanshu Mittal Maxim Tatarchenko Özgün Çiçek Thomas Brox VLM 19 59 0 11 Dec 2019
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