10 citations · 16 across the 10 of their papers we have counts for
10 papers
DINOv3 Beats Specialized Detectors: A Simple Foundation Model Baseline for Image Forensics
Jieming Yu, Qiuxiao Feng, Zhuohan Wang +1
With the rapid advancement of deep generative models, realistic fake images have become increasingly accessible, yet existing localization methods rely on complex designs and still…
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…
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…
Can We Get Rid of Handcrafted Feature Extractors? SparseViT: Nonsemantics-Centered, Parameter-Efficient Image Manipulation Localization through Spare-Coding Transformer
Lei Su, Xiaochen Ma, Xuekang Zhu +3
Non-semantic features or semantic-agnostic features, which are irrelevant to image context but sensitive to image manipulations, are recognized as evidential to Image Manipulation…
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…
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…
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…
Perceptual MAE for Image Manipulation Localization: A High-level Vision Learner Focusing on Low-level Features
Xiaochen Ma, Jizhe Zhou, Xiong Xu +2
Nowadays, multimedia forensics faces unprecedented challenges due to the rapid advancement of multimedia generation technology thereby making Image Manipulation Localization (IML)…
Pre-training-free Image Manipulation Localization through Non-Mutually Exclusive Contrastive Learning
Jizhe Zhou, Xiaochen Ma, Xia Du +2
Deep Image Manipulation Localization (IML) models suffer from training data insufficiency and thus heavily rely on pre-training. We argue that contrastive learning is more suitable…
IML-ViT: Benchmarking Image Manipulation Localization by Vision Transformer
Xiaochen Ma, Bo Du, Zhuohang Jiang +3
Advanced image tampering techniques are increasingly challenging the trustworthiness of multimedia, leading to the development of Image Manipulation Localization (IML). But what ma…