activity
20232025
most citedActPrompt: In-Domain Feature Adaptation via Action Cues for Video Temporal Grounding

1 citations · 2 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CV2025

Hierarchical Identity Learning for Unsupervised Visible-Infrared Person Re-Identification

Haonan Shi, Yubin Wang, De Cheng +3

Unsupervised visible-infrared person re-identification (USVI-ReID) aims to learn modality-invariant image features from unlabeled cross-modal person datasets by reducing the modali…

cs.CV2025

Exploring Interpretability for Visual Prompt Tuning with Cross-layer Concepts

Yubin Wang, Xinyang Jiang, De Cheng +4

Visual prompt tuning offers significant advantages for adapting pre-trained visual foundation models to specific tasks. However, current research provides limited insight into the…

cs.CV2024

UniDet: Unified and Universal Framework for Prompt-Guided Multi-dataset 3D Detection

Yubin Wang, Zhikang Zou, Xiaoqing Ye +3

We present UniDet, a brand new framework for unified and universal multi-dataset training on 3D detection, enabling robust performance across diverse domains and generalization…

cs.CV2024

HPT++: Hierarchically Prompting Vision-Language Models with Multi-Granularity Knowledge Generation and Improved Structure Modeling

Yubin Wang, Xinyang Jiang, De Cheng +3

Prompt learning has become a prevalent strategy for adapting vision-language foundation models (VLMs) such as CLIP to downstream tasks. With the emergence of large language models…

cs.CV2024★ 1 cited

ActPrompt: In-Domain Feature Adaptation via Action Cues for Video Temporal Grounding

Yubin Wang, Xinyang Jiang, De Cheng +2

Video temporal grounding is an emerging topic aiming to identify specific clips within videos. In addition to pre-trained video models, contemporary methods utilize pre-trained vis…

cs.CV2023★ 1 cited

Learning Hierarchical Prompt with Structured Linguistic Knowledge for Vision-Language Models

Yubin Wang, Xinyang Jiang, De Cheng +2

Prompt learning has become a prevalent strategy for adapting vision-language foundation models to downstream tasks. As large language models (LLMs) have emerged, recent studies hav…