30 citations · 43 across the 9 of their papers we have counts for
6 papers · 1 filter
UMFC: Unsupervised Multi-Domain Feature Calibration for Vision-Language Models
Jiachen Liang, Ruibing Hou, Minyang Hu +3
Pre-trained vision-language models (e.g., CLIP) have shown powerful zero-shot transfer capabilities. But they still struggle with domain shifts and typically require labeled data t…
UniPose: A Unified Multimodal Framework for Human Pose Comprehension, Generation and Editing
Yiheng Li, Ruibing Hou, Hong Chang +2
Human pose plays a crucial role in the digital age. While recent works have achieved impressive progress in understanding and generating human poses, they often support only a sing…
HERM: Benchmarking and Enhancing Multimodal LLMs for Human-Centric Understanding
Keliang Li, Zaifei Yang, Jiahe Zhao +5
The significant advancements in visual understanding and instruction following from Multimodal Large Language Models (MLLMs) have opened up more possibilities for broader applicati…
Clothes-Changing Person Re-Identification with Feasibility-Aware Intermediary Matching
Jiahe Zhao, Ruibing Hou, Hong Chang +4
Current clothes-changing person re-identification (re-id) approaches usually perform retrieval based on clothes-irrelevant features, while neglecting the potential of clothes-relev…
Task Attribute Distance for Few-Shot Learning: Theoretical Analysis and Applications
Minyang Hu, Hong Chang, Zong Guo +3
Few-shot learning (FSL) aims to learn novel tasks with very few labeled samples by leveraging experience from \emph{related} training tasks. In this paper, we try to understand FSL…
Progressive Conservative Adaptation for Evolving Target Domains
Gangming Zhao, Chaoqi Chen, Wenhao He +5
Conventional domain adaptation typically transfers knowledge from a source domain to a stationary target domain. However, in many real-world cases, target data usually emerge seque…