7 papers
Mono3DVG-EnSD: Enhanced Spatial-aware and Dimension-decoupled Text Encoding for Monocular 3D Visual Grounding
Yuzhen Li, Min Liu, Zhaoyang Li +4
Monocular 3D Visual Grounding (Mono3DVG) is an emerging task that locates 3D objects in RGB images using text descriptions with geometric cues. However, existing methods face two k…
A Dual-stage Prompt-driven Privacy-preserving Paradigm for Person Re-Identification
Ruolin Li, Min Liu, Yuan Bian +4
With growing concerns over data privacy, researchers have started using virtual data as an alternative to sensitive real-world images for training person re-identification (Re-ID)…
MIMO: A medical vision language model with visual referring multimodal input and pixel grounding multimodal output
Yanyuan Chen, Dexuan Xu, Yu Huang +6
Currently, medical vision language models are widely used in medical vision question answering tasks. However, existing models are confronted with two issues: for input, the model…
Dual Enhancement on 3D Vision-Language Perception for Monocular 3D Visual Grounding
Yuzhen Li, Min Liu, Yuan Bian +4
Monocular 3D visual grounding is a novel task that aims to locate 3D objects in RGB images using text descriptions with explicit geometry information. Despite the inclusion of geom…
Prompt-driven Transferable Adversarial Attack on Person Re-Identification with Attribute-aware Textual Inversion
Yuan Bian, Min Liu, Yunqi Yi +2
Person re-identification (re-id) models are vital in security surveillance systems, requiring transferable adversarial attacks to explore the vulnerabilities of them. Recently, vis…
Modality Unified Attack for Omni-Modality Person Re-Identification
Yuan Bian, Min Liu, Yunqi Yi +3
Deep learning based person re-identification (re-id) models have been widely employed in surveillance systems. Recent studies have demonstrated that black-box single-modality and c…