Skip to content

alex-xun-xu/LearnSubspaceMoSeg

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

5 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Learning Clustering for Motion Segmentation

Created by Xun Xu.

prediction example

Introduction

This is the official repository for Learning Clustering for Motion Segmentation [1] . We proposed a deep neural network based clustering framework to learned from labeled clustering dataset. Experiments are carried out on both rigid 3D motio segmentation and more challenging non-rigid motion segmentation benchmarks.

You can also replace the backbone network with PointNet , PointNet++ or other point cloud backbones.

We currently released tensorflow code for experiments on KT3DMoSeg dataset [2, 3]. If you can implement this algorithm in PyTorch I am very happy to provide the link to your repository. You are welcome to report any bugs you would identify. Should you have any concerns or experience any issues please raise in Issues so that all people can benefit from the discussions.

Installation

This code has been tested on Pyhon3.6, TensorFlow1.14, CUDA 10.0, cuDNN 7.0 and Ubuntu 18.04

Dataset

KT3DMoSeg

You should first download the data for KT3MoSeg from: https://www.dropbox.com/s/h6ub9pt9dk4j3h8/KT3DMoSegClips.zip?dl=0 . Then put the unzipped files under ./Dataset . The ./KT3DMoSeg/Seq contains the original clips and the ./KT3DMoSeg/Data contains all processed trajectories.

FBMS59

Please download the preprocessed trajectory files from: https://www.dropbox.com/s/x49dscvds1ugtqr/FBMS_Clips.zip?dl=0 . Then unzip the files to ./Dataset/FBMS/Data .

Usage

You can run the cross-validation experiment for KT3DMoSeg by running the following script. You only need to specify the GPU you want to use for training and keep all other hyperparameters unchanged.

cd ./KT3DMoSeg
GPU=0
python  CrossValid_KT3DMoSeg.py --GPU $GPU

To reproduce the results for FBMS59 please run the following script.

cd ./FBMS
GPU=0
# Train model
python train_FBMS.py --GPU $GPU --SaveMdl 1

# Test and export segmentation results 
# Replace XXX with the exact directory containing result, e.g. ../Results/FBMS/SubspaceNet50...
python test_FBMS_SOD.py --RsltPath XXX

# Evaluate Precision, Recall and Fmeasure
python Eval_PR_MdlSel_SOD.py

Reference

[1] Xun Xu, Loong-Fah Cheong, Zhuwen Li, Le Zhang and Ce Zhu. "Learning Clustering for Motion Segmentation." IEEE Transactions on Circuits and Systems for Video Technology (2021).

[2] Xun Xu, Loong-Fah Cheong, and Zhuwen Li. "Motion segmentation by exploiting complementary geometric models." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2018.

[3] Xun Xu, Loong Fah Cheong, and Zhuwen Li. "3D Rigid Motion Segmentation with Mixed and Unknown Number of Models." IEEE Transactions on Pattern Analysis and Machine Intelligence (2019).

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Languages