7 papers · 1 filter
Trustworthy synthetic visual media: Evidence across the media lifecycle
Zexi Jia, Zhiqiang Yuan, Jie Zhou +1
Images and videos have long helped people understand what happened and how a work came into being. Generative systems complicate that role. Realistic media can now be produced and…
CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection
Zexi Jia, Zhiqiang Yuan, Xiaoyue Duan +3
AI-generated image detection faces a persistent trade-off between generalization and efficiency: lightweight artifact-based methods often degrade on unseen generators or domains, w…
Manifold-Optimal Guidance: A Unified Riemannian Control View of Diffusion Guidance
Zexi Jia, Pengcheng Luo, Zhengyao Fang +2
Classifier-Free Guidance (CFG) serves as the de facto control mechanism for conditional diffusion, yet high guidance scales notoriously induce oversaturation, texture artifacts, an…
Evaluating Generative Models via One-Dimensional Code Distributions
Zexi Jia, Pengcheng Luo, Yijia Zhong +2
Most evaluations of generative models rely on feature-distribution metrics such as FID, which operate on continuous recognition features that are explicitly trained to be invariant…
Too Vivid to Be Real? Benchmarking and Calibrating Generative Color Fidelity
Zhengyao Fang, Zexi Jia, Yijia Zhong +5
Recent advances in text-to-image (T2I) generation have greatly improved visual quality, yet producing images that appear visually authentic to real-world photography remains challe…
StyleDecoupler: Generalizable Artistic Style Disentanglement
Zexi Jia, Jinchao Zhang, Jie Zhou
Representing artistic style is challenging due to its deep entanglement with semantic content. We propose StyleDecoupler, an information-theoretic framework that leverages a key in…
F2RVLM: Boosting Fine-grained Fragment Retrieval for Multi-Modal Long-form Dialogue with Vision Language Model
Hanbo Bi, Zhiqiang Yuan, Zexi Jia +6
Traditional dialogue retrieval aims to select the most appropriate utterance or image from recent dialogue history. However, they often fail to meet users' actual needs for revisit…