Track 1 is for the detection and recognition of airplanes in optical remote sensing images. For each image in the dataset, there is an XML file with the same name for describing annotation information. Each airplane instance in images is annotated by the corresponding category information and location with an oriented bounding box.
Two-stage object detection method Faster RCNN based on ResNet-50 is developed for object detection tracks. For Track 1, add an angle information regression to realize rotated boxes regression.
It is modified from mmdetection. The master branch works with PyTorch 1.1 or higher.
- Linux
- Python 3.5+ (Say goodbye to Python2)
- PyTorch 1.1
- CUDA 9.0+
- NCCL 2+
- GCC 4.9+
- mmcv
The code will be available soon.
| Method | Result (mAP) |
|---|---|
| Faster RCNN | 48.42 |