Object Detection On Seadronessee
Metrics
mAP@0.5
Results
Performance results of various models on this benchmark
| Paper Title | ||
|---|---|---|
| Synth Pretrained Faster R-CNN ResNeXt-101-FPN | 59.20 | Leveraging Synthetic Data in Object Detection on Unmanned Aerial Vehicles |
| Synth Pretrained Yolo5 | 59.08 | Leveraging Synthetic Data in Object Detection on Unmanned Aerial Vehicles |
| Faster R-CNN ResNeXt-101-FPN | 54.66 | SeaDronesSee: A Maritime Benchmark for Detecting Humans in Open Water |
| CenterNet Hourglass104 | 50.32 | SeaDronesSee: A Maritime Benchmark for Detecting Humans in Open Water |
| Synth Pretrained EffDetD0 | 38.74 | Leveraging Synthetic Data in Object Detection on Unmanned Aerial Vehicles |
| EfficientDet D0 | 37.11 | SeaDronesSee: A Maritime Benchmark for Detecting Humans in Open Water |
| CenterNet ResNet101 | 36.42 | SeaDronesSee: A Maritime Benchmark for Detecting Humans in Open Water |
| Faster RCNN ResNet50FPN | 30.09 | SeaDronesSee: A Maritime Benchmark for Detecting Humans in Open Water |
| CenterNet ResNet18 | 21.84 | SeaDronesSee: A Maritime Benchmark for Detecting Humans in Open Water |
| Yolo 5 | - | Leveraging Synthetic Data in Object Detection on Unmanned Aerial Vehicles |
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