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Learning to Separate: Detecting Heavily-Occluded Objects in Urban Scenes
This repository is the official implementation of our ECCV 2020 paper: Learning to Separate: Detecting Heavily-Occluded Objects in Urban Scenes
Requirements
Environment: You only need to install Tensorflow 1.13, and some common-used tools like opencv-python and numpy.
Data:
KITTI: Download the dataset from KITTI. To run the code, you need to first split the dataset into training and validation set by yourself.(Random partition is OK.)
CityPersons: Download the images from CityScapes and the annotations from here. You can use the official validation set to test your model.
Usage
1. Training
% train KITTI
python bin/kitti/kitti_train.py --log True --gpu 0
% train CityPersons
python bin/citypersons/cp_trian.py --log True --gpu 0
2. Test
% test KITTI
python bin/kitti/kitti_test.py --gpu 0
% test CityPersons
python bin/citypersons/cp_test.py --gpu 0
Citation
@inproceedings{yang2020separate,
title={ Learning to Separate: Detecting Heavily-Occluded Objects in Urban Scenes},
author={Yang, Chenhongyi and Ablavsky, Vitaly and Wang, Kaihong and Feng, Qi and Betke, Margrit},
booktitle={ECCV},
year={2020}
}