1 citations · 2 across the 12 of their papers we have counts for
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Hierarchical Anti-Aesthetics: Protecting Facial Privacy against Customized Diffusion Models
Songping Wang, Yueming Lyu, Shiqi Liu +5
The rise of customized diffusion models has fueled a boom in personalized visual content creation, but it also introduces serious risks of malicious misuse, thereby posing threats…
Towards High Fidelity Face Swapping: A Comprehensive Survey and New Benchmark
Qi Li, Weining Wang, Shuangjun Du +5
Face swapping has witnessed significant progress in recent years, largely driven by advances in deep generative models such as GANs and diffusion models.Despite these advances, exi…
Revisiting MLLM Based Image Quality Assessment: Errors and Remedy
Zhenchen Tang, Songlin Yang, Bo Peng +2
The rapid progress of multi-modal large language models (MLLMs) has boosted the task of image quality assessment (IQA). However, a key challenge arises from the inherent mismatch b…
HandEval: Taking the First Step Towards Hand Quality Evaluation in Generated Images
Zichuan Wang, Bo Peng, Songlin Yang +2
Although recent text-to-image (T2I) models have significantly improved the overall visual quality of generated images, they still struggle in the generation of accurate details in…
DREAM: A Benchmark Study for Deepfake photoREalism AssessMent
Bo Peng, Zichuan Wang, Sheng Yu +3
Deep learning based face-swap videos, widely known as deepfakes, have drawn wide attention due to their threat to information credibility. Recent works mainly focus on the problem…
Concept Corrector: Erase concepts on the fly for text-to-image diffusion models
Zheling Meng, Bo Peng, Xiaochuan Jin +4
Text-to-image diffusion models have demonstrated the underlying risk of generating various unwanted content, such as sexual elements. To address this issue, the task of concept era…