Code for CVPR 2018 paper --- Texture Mapping for 3D Reconstruction with RGB-D Sensor

Overview

G2LTex

This repository contains the implementation of "Texture Mapping for 3D Reconstruction with RGB-D Sensor (CVPR2018)" based on mvs-texturing. Due to the agreement with other company, some parts can only be released in the form of .so files. More information and the paper can be found on our group website and Qingan's homepage.

Publication

If you find this code useful for your research, please cite our work:

Yanping Fu, Qingan Yan, Long Yang, Jie Liao, Chunxia Xiao. Texture Mapping for 3D Reconstruction with RGB-D Sensor. In CVPR. 2018.

@inproceedings{fu2018texture,
  title={Texture Mapping for 3D Reconstruction with RGB-D Sensor},
  author={Fu, Yanping and Yan, Qingan and Yang, Long and Liao, Jie and Xiao, Chunxia},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  pages={4645--4653},
  year={2018},
  organization={IEEE}
}

How to use

1. Run

To test our algorithm. run G2LTex in command line:

./bin/G2LTex [DIR] [PLY] 

Params explanation: -PLY: The reconstructed model for texture mapping. -DIR: The texture image directory, include rgb images, depth images, and camera trajectory.

The parameters of the camera and the system can be set in the config file.

Config/config.yml

How to install and run this code.

git clone https://github.com/fdp0525/G2LTex.git
cd G2LTex/bin
./G2LTex ../Data/bloster/textureimages ../Data/bloster/bloster.ply

We need to modify the configuration file config.yml before running the other datasets.

./G2LTex ../Data/apt0/apt0 ../Data/apt0/apt0.ply

2. Input Format

  • Color frames (color_XX.jpg): RGB, 24-bit, JPG.
  • Depth frames (depth_XX.png): depth (mm), 16-bit, PNG (invalid depth is set to 0).
  • Camera poses (color_XX.cam): world-to-camera [tx, ty, tz, R00, R01, R02, R10, R11, R12, R20, R21, R22].

3. Dependencies

The code has following prerequisites:

  • ubuntu 16.04
  • gcc (5.4.0)
  • OpenCV (2.4.10)
  • Eigen (>3.0)
  • png12
  • jpeg

4. Parameters

All the parameters can be set in the file Config/config.yml as follows:

%YAML:1.0
depth_fx: 540.69
depth_fy: 540.69
depth_cx: 479.75
depth_cy: 269.75
depth_width: 960
depth_height: 540

RGB_fx: 1081.37
RGB_fy: 1081.37
RGB_cx: 959.5
RGB_cy: 539.5
RGB_width: 1920
RGB_height: 1080
.
.
.

5. Results

Some precomputed results can be found in the folder results/.

Owner
Fu Yanping(付燕平)
Fu Yanping(付燕平)
SigOpt wrappers for scikit-learn methods

SigOpt + scikit-learn Interfacing This package implements useful interfaces and wrappers for using SigOpt and scikit-learn together Getting Started In

SigOpt 73 Sep 30, 2022
Automatic learning-rate scheduler

AutoLRS This is the PyTorch code implementation for the paper AutoLRS: Automatic Learning-Rate Schedule by Bayesian Optimization on the Fly published

Yuchen Jin 33 Nov 18, 2022
Official Pytorch implementation of "Unbiased Classification Through Bias-Contrastive and Bias-Balanced Learning (NeurIPS 2021)

Unbiased Classification Through Bias-Contrastive and Bias-Balanced Learning (NeurIPS 2021) Official Pytorch implementation of Unbiased Classification

Youngkyu 17 Jan 01, 2023
Official git repo for the CHIRP project

CHIRP Project This is the official git repository for the CHIRP project. Pull requests are accepted here, but for the moment, the main repository is s

Dan Smith 77 Jan 08, 2023
Occlusion robust 3D face reconstruction model in CFR-GAN (WACV 2022)

Occlusion Robust 3D face Reconstruction Yeong-Joon Ju, Gun-Hee Lee, Jung-Ho Hong, and Seong-Whan Lee Code for Occlusion Robust 3D Face Reconstruction

Yeongjoon 31 Dec 19, 2022
Revisiting Weakly Supervised Pre-Training of Visual Perception Models

SWAG: Supervised Weakly from hashtAGs This repository contains SWAG models from the paper Revisiting Weakly Supervised Pre-Training of Visual Percepti

Meta Research 134 Jan 05, 2023
LeViT a Vision Transformer in ConvNet's Clothing for Faster Inference

LeViT: a Vision Transformer in ConvNet's Clothing for Faster Inference This repository contains PyTorch evaluation code, training code and pretrained

Facebook Research 504 Jan 02, 2023
Torchyolo - Yolov3 ve Yolov4 modellerin Pytorch uygulamasıdır

TORCHYOLO : Yolo Modellerin Pytorch Uygulaması Yapılacaklar: Yolov3 model.py ve

Kadir Nar 3 Aug 22, 2022
Moiré Attack (MA): A New Potential Risk of Screen Photos [NeurIPS 2021]

Moiré Attack (MA): A New Potential Risk of Screen Photos [NeurIPS 2021] This repository is the official implementation of Moiré Attack (MA): A New Pot

Dantong Niu 22 Dec 24, 2022
This is the repository for Learning to Generate Piano Music With Sustain Pedals

SusPedal-Gen This is the official repository of Learning to Generate Piano Music With Sustain Pedals Demo Page Dataset The dataset used in this projec

Joann Ching 12 Sep 02, 2022
[BMVC 2021] Official PyTorch Implementation of Self-supervised learning of Image Scale and Orientation Estimation

Self-Supervised Learning of Image Scale and Orientation Estimation (BMVC 2021) This is the official implementation of the paper "Self-Supervised Learn

Jongmin Lee 17 Nov 10, 2022
Open source person re-identification library in python

Open-ReID Open-ReID is a lightweight library of person re-identification for research purpose. It aims to provide a uniform interface for different da

Tong Xiao 1.3k Jan 01, 2023
AIR^2 for Interaction Prediction

This is the repository for AIR^2 for Interaction Prediction. Explanation of the solution: Video: link License AIR is released under the Apache 2.0 lic

21 Sep 27, 2022
Machine Learning Model deployment for Container (TensorFlow Serving)

try_tf_serving ├───dataset │ ├───testing │ │ ├───paper │ │ ├───rock │ │ └───scissors │ └───training │ ├───paper │ ├───rock

Azhar Rizki Zulma 5 Jan 07, 2022
Sequential Model-based Algorithm Configuration

SMAC v3 Project Copyright (C) 2016-2018 AutoML Group Attention: This package is a reimplementation of the original SMAC tool (see reference below). Ho

AutoML-Freiburg-Hannover 778 Jan 05, 2023
An Implicit Function Theorem (IFT) optimizer for bi-level optimizations

iftopt An Implicit Function Theorem (IFT) optimizer for bi-level optimizations. Requirements Python 3.7+ PyTorch 1.x Installation $ pip install git+ht

The Money Shredder Lab 2 Dec 02, 2021
TensorFlow implementation for Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How

Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How TensorFlow implementation for Bayesian Modeling and Unce

Shen Lab at Texas A&M University 8 Sep 02, 2022
PyTorch module to use OpenFace's nn4.small2.v1.t7 model

OpenFace for Pytorch Disclaimer: This codes require the input face-images that are aligned and cropped in the same way of the original OpenFace. * I m

Pete Tae-hoon Kim 176 Dec 12, 2022
Classification of EEG data using Deep Learning

Graduation-Project Classification of EEG data using Deep Learning Epilepsy is the most common neurological disease in the world. Epilepsy occurs as a

Osman Alpaydın 5 Jun 24, 2022
Machine learning Bot detection technique, based on United States election dataset

Machine learning Bot detection technique, based on United States election dataset (2020). Current github repo provides implementation described in pap

Alexander Shevtsov 4 Nov 20, 2022