Pedestrian Detection On Dvtod
Métriques
mAP
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | mAP | Paper Title | Repository |
|---|---|---|---|
| YOLOv3 (Visible) | 34.5 | YOLOv3: An Incremental Improvement | - |
| YOLOv7 (Visible) | - | YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors | - |
| YOLOv6 (Visible) | 38.1 | YOLOv6: A Single-Stage Object Detection Framework for Industrial Applications | - |
| YOLOv3 (Thermal) | 82.7 | YOLOv3: An Incremental Improvement | - |
| YOLOv7 (Thermal) | - | YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors | - |
| CFT | 82.7 | Cross-Modality Fusion Transformer for Multispectral Object Detection | - |
| YOLOv6 (Thermal) | 84.4 | YOLOv6: A Single-Stage Object Detection Framework for Industrial Applications | - |
| CMX | 81.6 | CMX: Cross-Modal Fusion for RGB-X Semantic Segmentation with Transformers | - |
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