7 papers · 1 filter
SAPL: Semantic-Agnostic Prompt Learning in CLIP for Weakly Supervised Image Manipulation Localization
Xinghao Wang, Changtao Miao, Dianmo Sheng +6
Malicious image manipulation threatens public safety and requires efficient localization methods. Existing approaches depend on costly pixel-level annotations which make training e…
GuardTrace-VL: Detecting Unsafe Multimodel Reasoning via Iterative Safety Supervision
Yuxiao Xiang, Junchi Chen, Zhenchao Jin +5
Multimodal large reasoning models (MLRMs) are increasingly deployed for vision-language tasks that produce explicit intermediate rationales. However, reasoning traces can contain u…
DDL: A Large-Scale Datasets for Deepfake Detection and Localization in Diversified Real-World Scenarios
Changtao Miao, Yi Zhang, Weize Gao +11
Recent advances in AIGC have exacerbated the misuse of malicious deepfake content, making the development of reliable deepfake detection methods an essential means to address this…
MFFI: Multi-Dimensional Face Forgery Image Dataset for Real-World Scenarios
Changtao Miao, Yi Zhang, Man Luo +9
Rapid advances in Artificial Intelligence Generated Content (AIGC) have enabled increasingly sophisticated face forgeries, posing a significant threat to social security. However,…
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…
Inclusion 2024 Global Multimedia Deepfake Detection Challenge: Towards Multi-dimensional Face Forgery Detection
Yi Zhang, Weize Gao, Changtao Miao +10
In this paper, we present the Global Multimedia Deepfake Detection held concurrently with the Inclusion 2024. Our Multimedia Deepfake Detection aims to detect automatic image and a…