Reliable evaluation of image forgery localization (IFL) requires assessing models under diverse distribution changes, yet existing benchmarks often cover limited manipulation conditions or entangle multiple factors in cross-dataset evaluation. Consequently, aggregate performance provides an incomplete view of localizat...
Bao-Ke Dou, Zi-Ye Wang, Hao Wang et al.· 0 citations
Camouflaged Object Detection (COD) aims to segment objects that are hidden within complex backgrounds. Due to the low visual contrast of camouflaged objects, annotations are costly, motivating unsupervised COD (UCOD) to eliminate labeling expenses. Most UCOD methods follow the “MLLMs + other foundation models + SAM” pa...
Hua-Feng Chen, Yueming Lyu, Caifeng Shan· Proceedings of the Thirty-Fi...· 0 citations
This work proposes MME-Safety, a rigorously verified benchmark featuring a unique four-dimensional annotation schema that categorizes risk scenarios, harm severity, and modality-specific stealth levels and introduces a hierarchical evaluation framework to assess fundamental response reliability, actual risk exposure, a...
Yi Shi, Yueming Lyu, Hao-Xiang Tan et al.· 0 citations
This work introduces PRMU, a benchmark for evaluating corpus-free multimodal unlearning under realistic person-centric deletion requests, and introduces Similarity-Gated Projection Editing (SGPE), a lightweight corpus-free unlearning baseline with knowledge displacement, protected parameter-space editing, and locality-...
Hua-Feng Chen, Yueming Lyu, Ziyuan Chen et al.· 0 citations
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