research
∙
06/30/2022
ProSelfLC: Progressive Self Label Correction Towards A Low-Temperature Entropy State
To train robust deep neural networks (DNNs), we systematically study sev...
share
research
∙
05/07/2020
ProSelfLC: Progressive Self Label Correction for Target Revising in Label Noise
In this work, we address robust deep learning under label noise (semi-su...
research
∙
11/22/2019
Instance Cross Entropy for Deep Metric Learning
Loss functions play a crucial role in deep metric learning thus a variet...
research
∙
11/20/2019
ID-aware Quality for Set-based Person Re-identification
Set-based person re-identification (SReID) is a matching problem that ai...
research
∙
05/27/2019
Emphasis Regularisation by Gradient Rescaling for Training Deep Neural Networks with Noisy Labels
It is fundamental and challenging to train robust and accurate Deep Neur...
research
∙
03/28/2019
Improving MAE against CCE under Label Noise
Label noise is inherent in many deep learning tasks when the training se...
research
∙
03/27/2019
GAN-based Pose-aware Regulation for Video-based Person Re-identification
Video-based person re-identification deals with the inherent difficulty ...
research
∙
03/08/2019
Ranked List Loss for Deep Metric Learning
The objective of deep metric learning (DML) is to learn embeddings that ...
research
∙
11/04/2018
