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SOTA
Image Manipulation Detection
Image Manipulation Detection On Casia V1
Image Manipulation Detection On Casia V1
Metrics
AUC
Balanced Accuracy
Results
Performance results of various models on this benchmark
Columns
Model Name
AUC
Balanced Accuracy
Paper Title
CAT-Net v2
.942
.838
Learning JPEG Compression Artifacts for Image Manipulation Detection and Localization
MVSS-Net
.932
.528
Image Manipulation Detection by Multi-View Multi-Scale Supervision
Late Fusion
.930
.860
MMFusion: Combining Image Forensic Filters for Visual Manipulation Detection and Localization
Early Fusion
.929
.845
MMFusion: Combining Image Forensic Filters for Visual Manipulation Detection and Localization
TruFor
.916
.813
TruFor: Leveraging all-round clues for trustworthy image forgery detection and localization
DF-Net
.906
-
DF-Net: The Digital Forensics Network for Image Forgery Detection
CR-CNN
.670
.481
Constrained R-CNN: A general image manipulation detection model
ManTraNet
.644
.500
ManTra-Net: Manipulation Tracing Network for Detection and Localization of Image Forgeries With Anomalous Features
SPAN
.480
.112
SPAN: Spatial Pyramid Attention Network for Image Manipulation Localization
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Image Manipulation Detection On Casia V1 | SOTA | HyperAI