3 papers
cs.CV2026
CO-EVO: Co-evolving Semantic Anchoring and Style Diversification for Federated DG-ReID
Fengchun Zhang, Qiang Ma, Liuyu Xiang +3
Federated domain generalization for person re-identification (FedDG-ReID) aims to collaboratively train a pedestrian retrieval model across multiple decentralized source domains su…
cs.CV2024
From Obstacles to Resources: Semi-supervised Learning Faces Synthetic Data Contamination
Zerun Wang, Jiafeng Mao, Liuyu Xiang +1
Semi-supervised learning (SSL) can improve model performance by leveraging unlabeled images, which can be collected from public image sources with low costs. In recent years, synth…
cs.CV2024
SCOMatch: Alleviating Overtrusting in Open-set Semi-supervised Learning
Zerun Wang, Liuyu Xiang, Lang Huang +3
Open-set semi-supervised learning (OSSL) leverages practical open-set unlabeled data, comprising both in-distribution (ID) samples from seen classes and out-of-distribution (OOD) s…