Bootstrapping the Relationship Between Images and Their Clean and Noisy Labels

17 October 2022

Papers citing "Bootstrapping the Relationship Between Images and Their Clean and Noisy Labels"

6 / 6 papers shown

Title
Relation Modeling and Distillation for Learning with Noisy Labels Xiaming Chen Junlin Zhang Zhuang Qi Xin Qi NoLa 24 0 0 30 May 2024
FlexMatch: Boosting Semi-Supervised Learning with Curriculum Pseudo Labeling Bowen Zhang Yidong Wang Wenxin Hou Hao Wu Jindong Wang Manabu Okumura T. Shinozaki AAML 221 862 0 15 Oct 2021
Meta Pseudo Labels Hieu H. Pham Zihang Dai Qizhe Xie Minh-Thang Luong Quoc V. Le VLM 248 656 0 23 Mar 2020
Improved Baselines with Momentum Contrastive Learning Xinlei Chen Haoqi Fan Ross B. Girshick Kaiming He SSL 238 3,367 0 09 Mar 2020
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results Antti Tarvainen Harri Valpola OOD MoMe 244 1,275 0 06 Mar 2017
Densely Connected Convolutional Networks Gao Huang Zhuang Liu L. V. D. van der Maaten Kilian Q. Weinberger PINN 3DV 247 36,356 0 25 Aug 2016