activity
20212025
most citedSegment and Complete: Defending Object Detectors against Adversarial Patch Attacks with Robust Patch Detection

6 citations · 9 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2025

Beyond Vulnerabilities: A Survey of Adversarial Attacks as Both Threats and Defenses in Computer Vision Systems

Zhongliang Guo, Yifei Qian, Yanli Li +6

Adversarial attacks against computer vision systems have emerged as a critical research area that challenges the fundamental assumptions about neural network robustness and securit…

cs.CV2025

My Face Is Mine, Not Yours: Facial Protection Against Diffusion Model Face Swapping

Hon Ming Yam, Zhongliang Guo, Chun Pong Lau

The proliferation of diffusion-based deepfake technologies poses significant risks for unauthorized and unethical facial image manipulation. While traditional countermeasures have…

cs.CV20233 cited

Whole-body Detection, Recognition and Identification at Altitude and Range

Siyuan Huang, Ram Prabhakar Kathirvel, Chun Pong Lau +1

In this paper, we address the challenging task of whole-body biometric detection, recognition, and identification at distances of up to 500m and large pitch angles of up to 50 degr…

cs.CV2023

Attribute-Guided Encryption with Facial Texture Masking

Chun Pong Lau, Jiang Liu, Rama Chellappa

The increasingly pervasive facial recognition (FR) systems raise serious concerns about personal privacy, especially for billions of users who have publicly shared their photos on…

cs.CV20216 cited

Segment and Complete: Defending Object Detectors against Adversarial Patch Attacks with Robust Patch Detection

Jiang Liu, Alexander Levine, Chun Pong Lau +2

Object detection plays a key role in many security-critical systems. Adversarial patch attacks, which are easy to implement in the physical world, pose a serious threat to state-of…