This repository contains the source code for the paper FBNet: Feedback Network for Point Cloud Completion. ECCV, 2022. Oral.
Our project is compatible with MVP_Benchmark project. The recommended environment requirements can be found in MVP_Benchmark
- Linux with Python >= 3.6
- We use pytorch=1.6
You can copy our project to the directory MVP_Benchmark/completion/ and run our demo as follows:
cd FBNet
sh run.shThe pretrain model on MVP (2048) dataset is available at FBNet_pre-trained, which get 5.05 CD-T error on MVP testset.
Training code will be released soon.
If you use FBNet in your research or wish to refer to the results published in the paper, please consider citing our paper.
@inproceedings{Yan2022FBNet,
title={FBNet: Feedback Network for Point Cloud Completion},
author={Xuejun Yan, Hongyu Yan, Jingjing Wang, Hang Du, Zhihong Wu, Di Xie, Shiliang Pu, Li Lu.},
booktitle={European Conference on Computer Vision},
year={2022},
}This project is released under the Apache 2.0 license. Other codes from open source repository follows the original distributive licenses.
Some code of this repository is borrowed from SnowflakeNet, pytorchpointnet++, ChamferDistancePytorch,MVP_Benchmark. We thank the authors for their great jobs!