Salvage Reusable Samples from Noisy Data for Robust Learning

Salvage Reusable Samples from Noisy Data for Robust Learning

6 August 2020

Jian Andrew Zhang

Papers citing "Salvage Reusable Samples from Noisy Data for Robust Learning"

18 / 18 papers shown

Title
Locating and Mitigating Gradient Conflicts in Point Cloud Domain Adaptation via Saliency Map Skewness Jiaqi Tang Yinsong Xu Qingchao Chen 3DPC 27 0 0 22 Apr 2025
Open set label noise learning with robust sample selection and margin-guided module Yuandi Zhao Qianxi Xia Yang Sun Zhijie Wen Liyan Ma Shihui Ying NoLa 44 0 0 08 Jan 2025
Foster Adaptivity and Balance in Learning with Noisy Labels Mengmeng Sheng Zeren Sun Tao Chen Shuchao Pang Yucheng Wang Yazhou Yao 29 2 0 03 Jul 2024
Unleashing the Potential of Open-set Noisy Samples Against Label Noise for Medical Image Classification Zehui Liao Shishuai Hu Yong-quan Xia 33 0 0 18 Jun 2024
Learning Discriminative Dynamics with Label Corruption for Noisy Label Detection Suyeon Kim Dongha Lee SeongKu Kang Sukang Chae Sanghwan Jang Hwanjo Yu 32 1 0 30 May 2024
Robust Pseudo-label Learning with Neighbor Relation for Unsupervised Visible-Infrared Person Re-Identification Xiangbo Yin Jiangming Shi Yachao Zhang Yang Lu Zhizhong Zhang Yuan Xie Yanyun Qu NoLa 19 11 0 09 May 2024
QMix: Quality-aware Learning with Mixed Noise for Robust Retinal Disease Diagnosis Junlin Hou Jilan Xu Rui Feng Hao Chen 23 0 0 08 Apr 2024
Group Benefits Instances Selection for Data Purification Zhenhuang Cai Chuanyi Zhang Dan Huang Yuanbo Chen Xiuyun Guan Yazhou Yao NoLa 43 0 0 23 Mar 2024
Learning with Imbalanced Noisy Data by Preventing Bias in Sample Selection Huafeng Liu Mengmeng Sheng Zeren Sun Yazhou Yao Xian-Sheng Hua H. Shen NoLa 13 6 0 17 Feb 2024
Differences Between Hard and Noisy-labeled Samples: An Empirical Study Mahsa Forouzesh Patrick Thiran NoLa 14 1 0 20 Jul 2023
Unlocking the Power of Open Set : A New Perspective for Open-Set Noisy Label Learning Wenhai Wan Xinrui Wang Ming-Kun Xie Shao-Yuan Li Sheng-Jun Huang Songcan Chen 25 8 0 07 May 2023
VEIL: Vetting Extracted Image Labels from In-the-Wild Captions for Weakly-Supervised Object Detection Arushi Rai Adriana Kovashka 19 0 0 16 Mar 2023
A Survey of Dataset Refinement for Problems in Computer Vision Datasets Zhijing Wan Zhixiang Wang CheukTing Chung Zheng Wang 23 8 0 21 Oct 2022
Webly Supervised Fine-Grained Recognition: Benchmark Datasets and An Approach Zeren Sun Yazhou Yao Xiu-Shen Wei Yongshun Zhang Fumin Shen Jianxin Wu Jian Andrew Zhang Heng Tao Shen 26 55 0 05 Aug 2021
Non-Salient Region Object Mining for Weakly Supervised Semantic Segmentation Yazhou Yao Tao Chen Guosen Xie Chuanyi Zhang Fumin Shen Qi Wu Zhenmin Tang Jian Andrew Zhang 26 190 0 26 Mar 2021
Jo-SRC: A Contrastive Approach for Combating Noisy Labels Yazhou Yao Zeren Sun Chuanyi Zhang Fumin Shen Qi Wu Jian Andrew Zhang Zhenmin Tang NoLa 25 133 0 24 Mar 2021
Semantically Meaningful Class Prototype Learning for One-Shot Image Semantic Segmentation Tao Chen G. Xie Yazhou Yao Qiong Wang Fumin Shen Zhenmin Tang Jian Andrew Zhang VLM 19 44 0 22 Feb 2021
Exploiting Web Images for Fine-Grained Visual Recognition by Eliminating Noisy Samples and Utilizing Hard Ones Huafeng Liu Chuanyi Zhang Yazhou Yao Xiu-Shen Wei Fumin Shen Jian Zhang Zhenmin Tang NoLa 17 1 0 23 Jan 2021