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cs.CV2026
FedBST: Bilateral Self-Training for Unsupervised Federated Classification
Aijing Yu, Kuangpu Guo, Jian Liang +1
Unsupervised federated learning with Vision-Language Models (e.g., CLIP) offers a promising solution for label-free classification, yet its performance often degrades under severe…
cs.CV2026
Refining Open-Vocabulary Semantic Segmentation via Regional Semantics and Visual Prototypes
Aijing Yu, Zhengbo Wang, Lijun Sheng +2
Contrastive Language-Image Pre-training (CLIP) has shown superior performance in the image-level open-vocabulary classification task, benefiting from its powerful alignment of visu…
cs.CV2019★ 1 cited
LAMP-HQ: A Large-Scale Multi-Pose High-Quality Database and Benchmark for NIR-VIS Face Recognition
Aijing Yu, Haoxue Wu, Huaibo Huang +2
Near-infrared-visible (NIR-VIS) heterogeneous face recognition matches NIR to corresponding VIS face images. However, due to the sensing gap, NIR images often lose some identity in…