PyTorch implementation of DeepUME: Learning the Universal Manifold Embedding for Robust Point Cloud Registration (BMVC 2021)

Related tags

Deep Learning point-cloud-registration 3d-computer-vision
Overview

DeepUME: Learning the Universal Manifold Embedding for Robust Point Cloud Registration

[video] [paper] [supplementary] [data] [thesis]

teaser-1

Introduction

Deep Universal Manifold Embedding (DeepUME) is a learning-based point cloud registration algorithm which achieves fast and accurate global regitration. This repository contains a basic PyTorch implementation of DeepUME. Please refer to our paper for more details.

Usage

This code has been tested on Python 3.6.13, PyTorch 1.4.0 and CUDA 10.1.

Prerequisite

  1. PyTorch=1.4.0: https://pytorch.org
  2. h5py
  3. open3d
  4. TensorboardX: https://github.com/lanpa/tensorboardX
  5. Download data to data/.

Training

python main.py --exp_name=deepume --noise=sampling

Testing

python main.py --exp_name=deepume --eval 
or
python main.py --exp_name=pretrained --eval --pretrained='pretrained/deepume.t7' --noise=zero_intersec --test_dataset=FAUST
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Comments
  • Information about rendering

    Information about rendering

    Hi all! Thanks for the interesting work! I wonder which package you used to render the amazing figures of your paper! Would it be possible to share the name of the package and provide additional info? Best regards and thanks in advance!

    opened by saltoricristiano 0
Owner
Natalie Lang
Natalie Lang
GitHub
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