Gaussian Combined Distance: A Generic Metric for Object Detection

This is the official code for the [GCD]. The method is accepted by the GRSL in 2025.

Installation

Requirements

• Linux
• Python 3.7 (Python 2 is not supported)
• PyTorch 1.5 or higher
• CUDA 10.1 or higher
• NCCL 2
• GCC(G++) 5.4 or higher
• mmcv-nwd==1.3.5
• cocoapi-aitod==12.0.3

Install

a. Create a conda virtual environment and activate it.

conda create -n gcd python=3.7 -y
conda activate gcd

b. Install PyTorch stable or nightly and torchvision following the official instructions, e.g.,

pip install torch==1.5.0+cu101 torchvision==0.6.0+cu101 -f https://download.pytorch.org/whl/torch_stable.html

c. Install MMCV-NWD

git clone https://github.com/jwwangchn/mmcv-nwd.git
cd mmcv-nwd
MMCV_WITH_OPS=1 pip install -e .  # package mmcv-full will be installed after this step
cd ../

d. Install COCOAPI-AITOD for Evaluating on AI-TOD dataset

pip install "git+https://github.com/jwwangchn/cocoapi-aitod.git#subdirectory=aitodpycocotools"

e. Install

# optional
pip install -r requirements.txt

python setup.py develop
# or "pip install -v -e ."

Prepare datasets

Please refer to AI-TOD for AI-TOD dataset.

Run

The GCD's config files are in [configs/gcd].

Please see MMDetection full tutorials with existing dataset for beginners.

Training on a single GPU

python tools/train.py configs/gcd/retinanet_r50_aitodv2_gcd_1x.py

Benchmark

The benchmark and trained models will be publicly available soon.

Citation

@ARTICLE{gcd2025,
  author={Guan, Ziqian and Fu, Xieyi and Huang, Pengjun and Zhang, Hengyuan and Du, Hubin and Liu, Yongtao and Wang, Yinglin and Ma, Qang},
  journal={IEEE Geoscience and Remote Sensing Letters}, 
  title={Gaussian Combined Distance: A Generic Metric for Object Detection}, 
  year={2025},
  volume={22},
  number={},
  pages={1-5},
  keywords={Measurement;Object detection;Feature extraction;Optimization;Detectors;Geoscience and remote sensing;Accuracy;Training;Sensitivity;Convergence;Generic metric;tiny object detection},
  doi={10.1109/LGRS.2025.3531970}}