Multispectral Object Detection On Flir 1
평가 지표
mAP
mAP50
평가 결과
이 벤치마크에서 각 모델의 성능 결과
비교 표
| 모델 이름 | mAP | mAP50 |
|---|---|---|
| multimodal-object-detection-by-channel | 37.9% | 75.5% |
| cross-modality-fusion-transformer-for | - | 77.7% |
| when-pedestrian-detection-meets-multi-modal | - | 86.4% |
| 모델 4 | 50.5% | 85.5% |
| unirgb-ir-a-unified-framework-for-visible | 44.1% | 81.4% |
| multimodal-object-detection-by-channel | 41.3% | 79.2% |
| cross-modality-fusion-transformer-for | - | 73.9% |
| cross-modality-fusion-transformer-for | - | 67.8% |
| guided-attentive-feature-fusion-for | - | 72.9% |
| cmx-cross-modal-fusion-for-rgb-x-semantic | - | 82.2% |
| mipa-mixed-patch-infrared-visible-modality | 44.8% | 81.3% |
| rgb-x-object-detection-via-scene-specific | 47.1% | 86.16% |
| guided-attentive-feature-fusion-for | - | 72.7% |
| multimodal-object-detection-by-channel | 37.4% | 74.6% |
| removal-and-selection-improving-rgb-infrared | 43.8% | 83.9% |
| multispectral-fusion-for-object-detection | - | 71.2% |
| multimodal-object-detection-by-channel | 35.8% | - |
| multispectral-fusion-for-object-detection | - | 72.4% |