4 papers
PapMOT: Exploring Adversarial Patch Attack against Multiple Object Tracking
Jiahuan Long, Tingsong Jiang, Wen Yao +5
Tracking multiple objects in a continuous video stream is crucial for many computer vision tasks. It involves detecting and associating objects with their respective identities acr…
Robust SAM: On the Adversarial Robustness of Vision Foundation Models
Jiahuan Long, Zhengqin Xu, Tingsong Jiang +4
The Segment Anything Model (SAM) is a widely used vision foundation model with diverse applications, including image segmentation, detection, and tracking. Given SAM's wide applica…
CDUPatch: Color-Driven Universal Adversarial Patch Attack for Dual-Modal Visible-Infrared Detectors
Jiahuan Long, Wen Yao, Tingsong Jiang +1
Adversarial patches are widely used to evaluate the robustness of object detection systems in real-world scenarios. These patches were initially designed to deceive single-modal de…
Parameter-Free Fine-tuning via Redundancy Elimination for Vision Foundation Models
Jiahuan Long, Tingsong Jiang, Wen Yao +5
Vision foundation models (VFMs) have demonstrated remarkable capabilities in learning universal visual representations. However, adapting these models to downstream tasks conventio…