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20232026
most citedArtwork Protection Against Neural Style Transfer Using Locally Adaptive Adversarial Color Attack

10 citations · 16 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2026

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…

cs.CV2024★ 5 cited

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…

cs.CV2024★ 10 cited

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…

cs.CV2023★ 1 cited

Semi-Supervised Crowd Counting with Contextual Modeling: Facilitating Holistic Understanding of Crowd Scenes

Yifei Qian, Xiaopeng Hong, Zhongliang Guo +2

To alleviate the heavy annotation burden for training a reliable crowd counting model and thus make the model more practicable and accurate by being able to benefit from more data,…

cs.CV2023

A White-Box False Positive Adversarial Attack Method on Contrastive Loss Based Offline Handwritten Signature Verification Models

Zhongliang Guo, Weiye Li, Yifei Qian +2

In this paper, we tackle the challenge of white-box false positive adversarial attacks on contrastive loss based offline handwritten signature verification models. We propose a nov…