1 citations · 1 across the 3 of their papers we have counts for
9 papers
Thermal-Only Crowd Counting with Deployment-Time Privacy Protection
Yifei Qian, Zhongliang Guo, Chun Tong Lei +4
While RGB-Thermal crowd counting has shown promise, the paradigm faces critical limitations: RGB data raises privacy concerns in public surveillance, and multi-modal misalignment d…
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…
T2ICount: Enhancing Cross-modal Understanding for Zero-Shot Counting
Yifei Qian, Zhongliang Guo, Bowen Deng +5
Zero-shot object counting aims to count instances of arbitrary object categories specified by text descriptions. Existing methods typically rely on vision-language models like CLIP…
A Gray-box Attack against Latent Diffusion Model-based Image Editing by Posterior Collapse
Zhongliang Guo, Chun Tong Lei, Lei Fang +7
Recent advancements in Latent Diffusion Models (LDMs) have revolutionized image synthesis and manipulation, raising significant concerns about data misappropriation and intellectua…
DiffX: Guide Your Layout to Cross-Modal Generative Modeling
Zeyu Wang, Jingyu Lin, Yifei Qian +8
Diffusion models have made significant strides in language-driven and layout-driven image generation. However, most diffusion models are limited to visible RGB image generation. In…
Artwork Protection Against Neural Style Transfer Using Locally Adaptive Adversarial Color Attack
Zhongliang Guo, Junhao Dong, Yifei Qian +7
Neural style transfer (NST) generates new images by combining the style of one image with the content of another. However, unauthorized NST can exploit artwork, raising concerns ab…