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cs.CV2026

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…

cs.CV2025

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…

cs.CV2025

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,…

cs.CV2025

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…

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

Context-Aware Weakly Supervised Image Manipulation Localization with SAM Refinement

Xinghao Wang, Tao Gong, Qi Chu +2

Malicious image manipulation poses societal risks, increasing the importance of effective image manipulation detection methods. Recent approaches in image manipulation detection ha…