Image Manipulation Detection On Coverage
평가 지표
AUC
Balanced Accuracy
평가 결과
이 벤치마크에서 각 모델의 성능 결과
모델 이름 | AUC | Balanced Accuracy | Paper Title | Repository |
|---|---|---|---|---|
| SPAN | .670 | .235 | SPAN: Spatial Pyramid Attention Network for Image Manipulation Localization | |
| Early Fusion | .839 | .770 | MMFusion: Combining Image Forensic Filters for Visual Manipulation Detection and Localization | |
| ManTraNet | .760 | .500 | ManTra-Net: Manipulation Tracing Network for Detection and Localization of Image Forgeries With Anomalous Features | |
| MVSS-Net | .733 | .514 | Image Manipulation Detection by Multi-View Multi-Scale Supervision | |
| TruFor | .770 | .680 | TruFor: Leveraging all-round clues for trustworthy image forgery detection and localization | - |
| Late Fusion | .792 | .720 | MMFusion: Combining Image Forensic Filters for Visual Manipulation Detection and Localization | |
| CAT-Net v2 | .680 | .635 | Learning JPEG Compression Artifacts for Image Manipulation Detection and Localization | |
| CR-CNN | .553 | .391 | Constrained R-CNN: A general image manipulation detection model | - |
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