Object Detection On Waterscenes
Métriques
mAP@50-95
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | mAP@50-95 | Paper Title | Repository |
|---|---|---|---|
| Achelous-MV-GDF-S2 | 56.0 | Achelous: A Fast Unified Water-surface Panoptic Perception Framework based on Fusion of Monocular Camera and 4D mmWave Radar | |
| YOLOv8-M | 59.2 | WaterScenes: A Multi-Task 4D Radar-Camera Fusion Dataset and Benchmarks for Autonomous Driving on Water Surfaces | |
| YOLOX-M | 57.8 | YOLOX: Exceeding YOLO Series in 2021 | |
| Faster R-CNN | 47.8 | WaterScenes: A Multi-Task 4D Radar-Camera Fusion Dataset and Benchmarks for Autonomous Driving on Water Surfaces |
0 of 4 row(s) selected.