Object Detection On Pku Ddd17 Car
Metriken
mAP50
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Vergleichstabelle
| Modellname | mAP50 |
|---|---|
| eca-net-efficient-channel-attention-for-deep | 82.2 |
| cbam-convolutional-block-attention-module | 81.9 |
| calibrated-rgb-d-salient-object-detection | 83.4 |
| cmx-cross-modal-fusion-for-rgb-x-semantic | 80.4 |
| mefnet-multi-scale-event-fusion-network-for | 83.0 |
| bi-directional-cross-modality-feature | 82.0 |
| fusing-event-based-and-rgb-camera-for-robust | 81.9 |
| ssd-single-shot-multibox-detector | 73.1 |
| specificity-preserving-rgb-d-saliency | 84.7 |
| embracing-events-and-frames-with-hierarchical | 86.7 |
| squeeze-and-excitation-networks | 81.6 |
| rgb-event-fusion-for-moving-object-detection | 81.4 |
| yolov4-optimal-speed-and-accuracy-of-object | 81.3 |
| combining-events-and-frames-using-recurrent | 79.6 |