research
∙
05/23/2023
Decoupled Kullback-Leibler Divergence Loss
In this paper, we delve deeper into the Kullback-Leibler (KL) Divergence...
share
research
∙
03/21/2023
Learning Context-aware Classifier for Semantic Segmentation
Semantic segmentation is still a challenging task for parsing diverse co...
research
∙
01/03/2023
Understanding Imbalanced Semantic Segmentation Through Neural Collapse
A recent study has shown a phenomenon called neural collapse in that the...
research
∙
09/26/2022
Generalized Parametric Contrastive Learning
In this paper, we propose the Generalized Parametric Contrastive Learnin...
research
∙
03/22/2022
Rebalanced Siamese Contrastive Mining for Long-Tailed Recognition
Deep neural networks perform poorly on heavily class-imbalanced datasets...
research
∙
10/15/2021
Adversarial Attacks on ML Defense Models Competition
Due to the vulnerability of deep neural networks (DNNs) to adversarial e...
research
∙
07/26/2021
Parametric Contrastive Learning
In this paper, we propose Parametric Contrastive Learning (PaCo) to tack...
research
∙
04/01/2021
Improving Calibration for Long-Tailed Recognition
Deep neural networks may perform poorly when training datasets are heavi...
research
∙
01/26/2021
ResLT: Residual Learning for Long-tailed Recognition
Deep learning algorithms face great challenges with long-tailed data dis...
research
∙
11/23/2020