Exploiting Negative Learning for Implicit Pseudo Label Rectification in Source-Free Domain Adaptive Semantic Segmentation

23 June 2021

Papers citing "Exploiting Negative Learning for Implicit Pseudo Label Rectification in Source-Free Domain Adaptive Semantic Segmentation"

7 / 7 papers shown

Title
Trust And Balance: Few Trusted Samples Pseudo-Labeling and Temperature Scaled Loss for Effective Source-Free Unsupervised Domain Adaptation Andrea Maracani Lorenzo Rosasco Lorenzo Natale 165 0 0 01 Sep 2024
Bidirectional Uncertainty-Based Active Learning for Open Set Annotation Chen-Chen Zong Ye-Wen Wang Hai-Jian Ke Hai-Bo Ye Sheng-Jun Huang EDL 242 6 0 23 Feb 2024
A Comprehensive Survey on Test-Time Adaptation under Distribution ShiftsInternational Journal of Computer Vision (IJCV), 2023 Jian Liang Ran He Tien-Ping Tan OOD VLM TTA 251 349 0 27 Mar 2023
Source-Free Unsupervised Domain Adaptation: A SurveyNeural Networks (NN), 2022 Yuqi Fang P. Yap W. Lin Hongtu Zhu Mingxia Liu 383 131 0 31 Dec 2022
PASTA: Proportional Amplitude Spectrum Training Augmentation for Syn-to-Real Domain GeneralizationIEEE International Conference on Computer Vision (ICCV), 2022 Prithvijit Chattopadhyay Kartik Sarangmath Vivek Vijaykumar Judy Hoffman 282 42 0 02 Dec 2022
Pre-training Language Models with Deterministic Factual KnowledgeConference on Empirical Methods in Natural Language Processing (EMNLP), 2022 Shaobo Li Xiaoguang Li Lifeng Shang Chengjie Sun Bingquan Liu Zhenzhou Ji Xin Jiang Qun Liu KELM 153 14 0 20 Oct 2022
Data-Free Knowledge Transfer: A Survey Yuang Liu Wei Zhang Jun Wang Jianyong Wang 195 54 0 31 Dec 2021