5 papers
FOCA: Frequency-Oriented Cross-Domain Forgery Detection, Localization and Explanation via Multi-Modal Large Language Model
Zhou Liu, Tonghua Su, Hongshi Zhang +4
Advances in image tampering techniques, particularly generative models, pose significant challenges to media verification, digital forensics, and public trust. Existing image forge…
Salvaging the Overlooked: Leveraging Class-Aware Contrastive Learning for Multi-Class Anomaly Detection
Lei Fan, Junjie Huang, Donglin Di +4
For anomaly detection (AD), early approaches often train separate models for individual classes, yielding high performance but posing challenges in scalability and resource managem…
Prototype-Based Image Prompting for Weakly Supervised Histopathological Image Segmentation
Qingchen Tang, Lei Fan, Maurice Pagnucco +1
Weakly supervised image segmentation with image-level labels has drawn attention due to the high cost of pixel-level annotations. Traditional methods using Class Activation Maps (C…
Interpretable Image Classification via Non-parametric Part Prototype Learning
Zhijie Zhu, Lei Fan, Maurice Pagnucco +1
Classifying images with an interpretable decision-making process is a long-standing problem in computer vision. In recent years, Prototypical Part Networks has gained traction as a…
MANTA: A Large-Scale Multi-View and Visual-Text Anomaly Detection Dataset for Tiny Objects
Lei Fan, Dongdong Fan, Zhiguang Hu +5
We present MANTA, a visual-text anomaly detection dataset for tiny objects. The visual component comprises over 137.3K images across 38 object categories spanning five typical doma…