6 papers
Can We Build a Monolithic Model for Fake Image Detection? SICA: Semantic-Induced Constrained Adaptation for Unified-Yet-Discriminative Artifact Feature Space Reconstruction
Bo Du, Xiaochen Ma, Xuekang Zhu +8
Fake Image Detection (FID), aiming at unified detection across four image forensic subdomains, is critical in real-world forensic scenarios. Compared with ensemble approaches, mono…
Towards Generalized Image Manipulation Localization via Score-based Model
Yunfei Wang, Bo Du, Zhe Yang +4
With the rapid evolution of synthetic media, Image Manipulation Localization (IML) has emerged as a critical component in multimedia forensics for ensuring the integrity of digital…
ForensicHub: A Unified Benchmark & Codebase for All-Domain Fake Image Detection and Localization
Bo Du, Xuekang Zhu, Xiaochen Ma +6
The field of Fake Image Detection and Localization (FIDL) is highly fragmented, encompassing four domains: deepfake detection (Deepfake), image manipulation detection and localizat…
M^3:Manipulation Mask Manufacturer for Arbitrary-Scale Super-Resolution Mask
Xinyu Yang, Xiaochen Ma, Xuekang Zhu +5
In the field of image manipulation localization (IML), the small quantity and poor quality of existing datasets have always been major issues. A dataset containing various types of…
Mesoscopic Insights: Orchestrating Multi-scale & Hybrid Architecture for Image Manipulation Localization
Xuekang Zhu, Xiaochen Ma, Lei Su +7
The mesoscopic level serves as a bridge between the macroscopic and microscopic worlds, addressing gaps overlooked by both. Image manipulation localization (IML), a crucial techniq…
IMDL-BenCo: A Comprehensive Benchmark and Codebase for Image Manipulation Detection & Localization
Xiaochen Ma, Xuekang Zhu, Lei Su +8
A comprehensive benchmark is yet to be established in the Image Manipulation Detection & Localization (IMDL) field. The absence of such a benchmark leads to insufficient and mislea…