Image Manipulation Detection On Columbia
평가 지표
AUC
Balanced Accuracy
평가 결과
이 벤치마크에서 각 모델의 성능 결과
비교 표
| 모델 이름 | AUC | Balanced Accuracy |
|---|---|---|
| trufor-leveraging-all-round-clues-for | .996 | .984 |
| constrained-r-cnn-a-general-image | .755 | .631 |
| learning-jpeg-compression-artifacts-for-image | .977 | .803 |
| mantra-net-manipulation-tracing-network-for | .810 | .500 |
| df-net-the-digital-forensics-network-for | 0.880 | - |
| exploring-multi-modal-fusion-for-image | .977 | .822 |
| image-manipulation-detection-by-multi-view | .984 | .729 |
| exploring-multi-modal-fusion-for-image | .996 | .962 |