1 citations · 1 across the 3 of their papers we have counts for
5 papers
Domain-Division based Progressive Learning for Source-Free Domain Adaptation
Pan Liu, Jing Li, Meng Zhao +3
With growing privacy and portability concerns, source-free domain adaptation requires only a source pre-trained model and an unlabeled target domain, allowing for effective adaptat…
LFM: Leveraging Foundation Models for Source-Free Universal Domain Adaptation
Jing Li, Pan Liu, Meng Zhao +7
Source-free universal domain adaptation (SF-UniDA) adapts a pre-trained source model to an unlabeled target domain under both covariate and label shifts, without access to source d…
Adaptive Dual-Teacher Distillation with Subnetwork Rectification for Bridging Semantic Gaps in Black-Box Domain Adaptation
Zhe Zhang, Jing Li, Wanli Xue +4
Assuming that neither source data nor source model parameters are accessible, black-box domain adaptation (BBDA) represents a highly practical yet challenging setting, where transf…
Imitation Learning Policy based on Multi-Step Consistent Integration Shortcut Model
Yu Fang, Xinyu Wang, Xuehe Zhang +4
The wide application of flow-matching methods has greatly promoted the development of robot imitation learning. However, these methods all face the problem of high inference time.…
Denoising-Contrastive Alignment for Continuous Sign Language Recognition
Leming Guo, Wanli Xue, Shengyong Chen
Continuous sign language recognition (CSLR) aims to recognize signs in untrimmed sign language videos to textual glosses. A key challenge of CSLR is achieving effective cross-modal…