4 papers
Ambiguity-Guided Learnable Distribution Calibration for Semi-Supervised Few-Shot Class-Incremental Learning
Fan Lyu, Linglan Zhao, Chengyan Liu +5
Few-Shot Class-Incremental Learning (FSCIL) focuses on models learning new concepts from limited data while retaining knowledge of previous classes. Recently, many studies have sta…
Test-Time Discovery via Hashing Memory
Fan Lyu, Tianle Liu, Zhang Zhang +2
We introduce Test-Time Discovery (TTD) as a novel task that addresses class shifts during testing, requiring models to simultaneously identify emerging categories while preserving…
Conformal Uncertainty Indicator for Continual Test-Time Adaptation
Fan Lyu, Hanyu Zhao, Ziqi Shi +4
Continual Test-Time Adaptation (CTTA) aims to adapt models to sequentially changing domains during testing, relying on pseudo-labels for self-adaptation. However, incorrect pseudo-…
MCRL4OR: Multimodal Contrastive Representation Learning for Off-Road Environmental Perception
Yi Yang, Zhang Zhang, Liang Wang
Most studies on environmental perception for autonomous vehicles (AVs) focus on urban traffic environments, where the objects/stuff to be perceived are mainly from man-made scenes…