59 citations · 138 across the 21 of their papers we have counts for
4 papers · 1 filter
HAP: Structure-Aware Masked Image Modeling for Human-Centric Perception
Junkun Yuan, Xinyu Zhang, Hao Zhou +12
Model pre-training is essential in human-centric perception. In this paper, we first introduce masked image modeling (MIM) as a pre-training approach for this task. Upon revisiting…
Quantitatively Measuring and Contrastively Exploring Heterogeneity for Domain Generalization
Yunze Tong, Junkun Yuan, Min Zhang +4
Domain generalization (DG) is a prevalent problem in real-world applications, which aims to train well-generalized models for unseen target domains by utilizing several source doma…
Universal Domain Adaptation via Compressive Attention Matching
Didi Zhu, Yincuan Li, Junkun Yuan +3
Universal domain adaptation (UniDA) aims to transfer knowledge from the source domain to the target domain without any prior knowledge about the label set. The challenge lies in ho…
Task-Oriented Multi-Modal Mutual Leaning for Vision-Language Models
Sifan Long, Zhen Zhao, Junkun Yuan +5
Prompt learning has become one of the most efficient paradigms for adapting large pre-trained vision-language models to downstream tasks. Current state-of-the-art methods, like CoO…