5 papers
Self-Reinforcing Prototype Evolution with Dual-Knowledge Cooperation for Semi-Supervised Lifelong Person Re-Identification
Kunlun Xu, Fan Zhuo, Jiangmeng Li +2
Current lifelong person re-identification (LReID) methods predominantly rely on fully labeled data streams. However, in real-world scenarios where annotation resources are limited,…
Componential Prompt-Knowledge Alignment for Domain Incremental Learning
Kunlun Xu, Xu Zou, Gang Hua +1
Domain Incremental Learning (DIL) aims to learn from non-stationary data streams across domains while retaining and utilizing past knowledge. Although prompt-based methods effectiv…
STOP: Integrated Spatial-Temporal Dynamic Prompting for Video Understanding
Zichen Liu, Kunlun Xu, Bing Su +3
Pre-trained on tremendous image-text pairs, vision-language models like CLIP have demonstrated promising zero-shot generalization across numerous image-based tasks. However, extend…
SCAP: Transductive Test-Time Adaptation via Supportive Clique-based Attribute Prompting
Chenyu Zhang, Kunlun Xu, Zichen Liu +2
Vision-language models (VLMs) encounter considerable challenges when adapting to domain shifts stemming from changes in data distribution. Test-time adaptation (TTA) has emerged as…
DASK: Distribution Rehearsing via Adaptive Style Kernel Learning for Exemplar-Free Lifelong Person Re-Identification
Kunlun Xu, Chenghao Jiang, Peixi Xiong +2
Lifelong person re-identification (LReID) is an important but challenging task that suffers from catastrophic forgetting due to significant domain gaps between training steps. Exis…