activity
20222026
most citedMulti-domain Learning for Updating Face Anti-spoofing Models

5 citations · 11 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CV2026

FusionAgent: A Multimodal Agent with Dynamic Model Selection for Human Recognition

Jie Zhu, Xiao Guo, Yiyang Su +2

Model fusion is a key strategy for robust recognition in unconstrained scenarios, as different models provide complementary strengths. This is especially important for whole-body h…

cs.CV2026

On the Holistic Approach for Detecting Human Image Forgery

Xiao Guo, Jie Zhu, Anil Jain +1

The rapid advancement of AI-generated content (AIGC) has escalated the threat of deepfakes, from facial manipulations to the synthesis of entire photorealistic human bodies. Howeve…

cs.CV2025

TalkingHeadBench: A Multi-Modal Benchmark & Analysis of Talking-Head DeepFake Detection

Xinqi Xiong, Prakrut Patel, Qingyuan Fan +6

The rapid advancement of talking-head deepfake generation fueled by advanced generative models has elevated the realism of synthetic videos to a level that poses substantial risks…

cs.CV2025

Benchmarking Unified Face Attack Detection via Hierarchical Prompt Tuning

Ajian Liu, Haocheng Yuan, Xiao Guo +13

PAD and FFD are proposed to protect face data from physical media-based Presentation Attacks and digital editing-based DeepFakes, respectively. However, isolated training of these…

cs.CV2025

Rethinking Vision-Language Model in Face Forensics: Multi-Modal Interpretable Forged Face Detector

Xiao Guo, Xiufeng Song, Yue Zhang +2

Deepfake detection is a long-established research topic vital for mitigating the spread of malicious misinformation. Unlike prior methods that provide either binary classification…

cs.CV2024★ 1 cited

Language-guided Hierarchical Fine-grained Image Forgery Detection and Localization

Xiao Guo, Xiaohong Liu, Iacopo Masi +1

Differences in forgery attributes of images generated in CNN-synthesized and image-editing domains are large, and such differences make a unified image forgery detection and locali…

cs.CV2024★ 1 cited

On Learning Multi-Modal Forgery Representation for Diffusion Generated Video Detection

Xiufeng Song, Xiao Guo, Jiache Zhang +5

Large numbers of synthesized videos from diffusion models pose threats to information security and authenticity, leading to an increasing demand for generated content detection. Ho…

cs.MM2024

Towards Effective User Attribution for Latent Diffusion Models via Watermark-Informed Blending

Yongyang Pan, Xiaohong Liu, Siqi Luo +5

Rapid advancements in multimodal large language models have enabled the creation of hyper-realistic images from textual descriptions. However, these advancements also raise signifi…

cs.CV2023★ 4 cited

Hierarchical Fine-Grained Image Forgery Detection and Localization

Xiao Guo, Xiaohong Liu, Zhiyuan Ren +3

Differences in forgery attributes of images generated in CNN-synthesized and image-editing domains are large, and such differences make a unified image forgery detection and locali…

cs.CV2022★ 5 cited

Multi-domain Learning for Updating Face Anti-spoofing Models

Xiao Guo, Yaojie Liu, Anil Jain +1

In this work, we study multi-domain learning for face anti-spoofing(MD-FAS), where a pre-trained FAS model needs to be updated to perform equally well on both source and target dom…