PyTorch implementation of the paper "SpSequenceNet: Semantic Segmentation Network on 4D Point Clouds" in CVPR 2020. Vedio Link: here
Python >= 3.6
PyTorch >= 1.3
numpy >= 1.17.2
sparseconvnet >= 0.2
tqdm
Training:
Firstly, the dataset setting is in the data_base and val_base of config.yaml. Modify it to the direction of your own dataset. Secondly, run as following:
cd train/semanticKITTI
python unet.py
Evaluation:
If you are validating your own trainined model, run as following:
cd train/semanticKITTI
python val_unet.py
If you want to use our trained model, add 'val_model_dir' under 'model' in the config.yaml. The val_model_dir is the directory of your model.
Our trained model is in here