7 papers
Multi-modal Test-time Adaptation via Adaptive Probabilistic Gaussian Calibration
Jinglin Xu, Yi Li, Chuxiong Sun +3
Multi-modal test-time adaptation (TTA) enhances the resilience of benchmark multi-modal models against distribution shifts by leveraging the unlabeled target data during inference.…
Test-Time Perturbation Learning with Delayed Feedback for Vision-Language-Action Models
Zehua Zang, Xi Wang, Fuchun Sun +4
Vision-Language-Action models (VLAs) achieve remarkable performance in sequential decision-making but remain fragile to subtle environmental shifts, such as small changes in object…
Vision-Language Attribute Disentanglement and Reinforcement for Lifelong Person Re-Identification
Kunlun Xu, Haotong Cheng, Jiangmeng Li +2
Lifelong person re-identification (LReID) aims to learn from varying domains to obtain a unified person retrieval model. Existing LReID approaches typically focus on learning from…
C^2Prompt: Class-aware Client Knowledge Interaction for Federated Continual Learning
Kunlun Xu, Yibo Feng, Jiangmeng Li +2
Federated continual learning (FCL) tackles scenarios of learning from continuously emerging task data across distributed clients, where the key challenge lies in addressing both te…
Doubly Debiased Test-Time Prompt Tuning for Vision-Language Models
Fei Song, Yi Li, Rui Wang +3
Test-time prompt tuning for vision-language models has demonstrated impressive generalization capabilities under zero-shot settings. However, tuning the learnable prompts solely ba…
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,…