1 citations · 3 across the 9 of their papers we have counts for
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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…
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…
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…
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…
DiffPhysBA: Diffusion-based Physical Backdoor Attack against Person Re-Identification in Real-World
Wenli Sun, Xinyang Jiang, Dongsheng Li +1
Person Re-Identification (ReID) systems pose a significant security risk from backdoor attacks, allowing adversaries to evade tracking or impersonate others. Beyond recognizing thi…
DROP: Decouple Re-Identification and Human Parsing with Task-specific Features for Occluded Person Re-identification
Shuguang Dou, Xiangyang Jiang, Yuanpeng Tu +4
The paper introduces the Decouple Re-identificatiOn and human Parsing (DROP) method for occluded person re-identification (ReID). Unlike mainstream approaches using global features…
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…