ShikunLi

ASL

Official Pytorch Implementation of: "Asymmetric Loss For Multi-Label Classification"(ICCV, 2021) paper

Awesome-Knowledge-Distillation

Awesome Knowledge-Distillation. 分类整理的知识蒸馏paper(2014-2021)。

Awesome-Learning-with-Label-Noise

A curated list of resources for Learning with Noisy Labels

Estimating_T_For_Noisy_Mutli-Labels

NeurIPS 2022: Estimating Noise Transition Matrix with Label Correlations for Noisy Multi-Label Learning

Imsg_Lab_homepage

ML-GCN

PyTorch implementation of Multi-Label Image Recognition with Graph Convolutional Networks, CVPR 2019.

MRNet

Code for CVPR 2021 paper. "Learning Calibrated Medical Image Segmentation via Multi-rater Agreement Modeling".

Sel-CL

CVPR 2022: Selective-Supervised Contrastive Learning with Noisy Labels

TAIDTM

TCL

IEEE TMM 2021: Trustable Co-label Learning from Multiple Noisy Annotators

ShikunLi/Sel-CL

CVPR 2022: Selective-Supervised Contrastive Learning with Noisy Labels

ShikunLi/Estimating_T_For_Noisy_Mutli-Labels

NeurIPS 2022: Estimating Noise Transition Matrix with Label Correlations for Noisy Multi-Label Learning

ShikunLi/TCL

IEEE TMM 2021: Trustable Co-label Learning from Multiple Noisy Annotators

ShikunLi/TAIDTM

ShikunLi/ASL

Official Pytorch Implementation of: "Asymmetric Loss For Multi-Label Classification"(ICCV, 2021) paper

ShikunLi/Awesome-Knowledge-Distillation

Awesome Knowledge-Distillation. 分类整理的知识蒸馏paper(2014-2021)。

ShikunLi/Awesome-Learning-with-Label-Noise

A curated list of resources for Learning with Noisy Labels

ShikunLi/Imsg_Lab_homepage

ShikunLi/ML-GCN

PyTorch implementation of Multi-Label Image Recognition with Graph Convolutional Networks, CVPR 2019.

ShikunLi/MRNet

Code for CVPR 2021 paper. "Learning Calibrated Medical Image Segmentation via Multi-rater Agreement Modeling".