ResearchTrend.AI
Exploiting Fine-Grained Prototype Distribution for Boosting Unsupervised Class Incremental Learning

Exploiting Fine-Grained Prototype Distribution for Boosting Unsupervised Class Incremental Learning

Jiaming Liu
Hongyuan Liu
Zhili Qin
Wei Han
Yulu Fan
Qinli Yang
Junming Shao
    CLL
ArXivPDFHTML

Papers citing "Exploiting Fine-Grained Prototype Distribution for Boosting Unsupervised Class Incremental Learning"

3 / 3 papers shown
Title
Multi-Granularity Class Prototype Topology Distillation for Class-Incremental Source-Free Unsupervised Domain Adaptation
Multi-Granularity Class Prototype Topology Distillation for Class-Incremental Source-Free Unsupervised Domain Adaptation
Peihua Deng
Jiehua Zhang
Xichun Sheng
C. Yan
Yaoqi Sun
Ying Fu
Liang-Sheng Li
CLL
76
1
0
25 Nov 2024
Towards Realistic Semi-Supervised Learning
Towards Realistic Semi-Supervised Learning
Mamshad Nayeem Rizve
Navid Kardan
M. Shah
49
44
0
05 Jul 2022
Emerging Properties in Self-Supervised Vision Transformers
Emerging Properties in Self-Supervised Vision Transformers
Mathilde Caron
Hugo Touvron
Ishan Misra
Hervé Jégou
Julien Mairal
Piotr Bojanowski
Armand Joulin
347
5,785
0
29 Apr 2021