1 citations · 1 across the 13 of their papers we have counts for
5 papers · 1 filter
SSR: Enhancing Depth Perception in Vision-Language Models via Rationale-Guided Spatial Reasoning
Yang Liu, Ming Ma, Xiaomin Yu +5
Despite impressive advancements in Visual-Language Models (VLMs) for multi-modal tasks, their reliance on RGB inputs limits precise spatial understanding. Existing methods for inte…
Rethinking Target Label Conditioning in Adversarial Attacks: A 2D Tensor-Guided Generative Approach
Hangyu Liu, Bo Peng, Pengxiang Ding +1
Compared to single-target adversarial attacks, multi-target attacks have garnered significant attention due to their ability to generate adversarial images for multiple target clas…
Enhancing Adversarial Transferability via Component-Wise Transformation
Hangyu Liu, Bo Peng, Can Cui +2
Deep Neural Networks (DNNs) are highly vulnerable to adversarial examples, which pose significant challenges in security-sensitive applications. Among various adversarial attack st…
ProFD: Prompt-Guided Feature Disentangling for Occluded Person Re-Identification
Can Cui, Siteng Huang, Wenxuan Song +3
To address the occlusion issues in person Re-Identification (ReID) tasks, many methods have been proposed to extract part features by introducing external spatial information. Howe…
PiTe: Pixel-Temporal Alignment for Large Video-Language Model
Yang Liu, Pengxiang Ding, Siteng Huang +3
Fueled by the Large Language Models (LLMs) wave, Large Visual-Language Models (LVLMs) have emerged as a pivotal advancement, bridging the gap between image and text. However, video…