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)
Random-Afg - Afghanistan Random Old Idz Cloner Tools

AFGHANISTAN RANDOM OLD IDZ CLONER TOOLS Install $ apt update $ apt upgrade $ apt

MAHADI HASAN AFRIDI 5 Jan 26, 2022
Keras implementation of Real-Time Semantic Segmentation on High-Resolution Images

Keras-ICNet [paper] Keras implementation of Real-Time Semantic Segmentation on High-Resolution Images. Training in progress! Requisites Python 3.6.3 K

Aitor Ruano 87 Dec 16, 2022
Group R-CNN for Point-based Weakly Semi-supervised Object Detection (CVPR2022)

Group R-CNN for Point-based Weakly Semi-supervised Object Detection (CVPR2022) By Shilong Zhang*, Zhuoran Yu*, Liyang Liu*, Xinjiang Wang, Aojun Zhou,

Shilong Zhang 129 Dec 24, 2022
Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers

Segmentation Transformer Implementation of Segmentation Transformer in PyTorch, a new model to achieve SOTA in semantic segmentation while using trans

Abhay Gupta 161 Dec 08, 2022
Non-Metric Space Library (NMSLIB): An efficient similarity search library and a toolkit for evaluation of k-NN methods for generic non-metric spaces.

Non-Metric Space Library (NMSLIB) Important Notes NMSLIB is generic but fast, see the results of ANN benchmarks. A standalone implementation of our fa

2.9k Jan 04, 2023
Neurolab is a simple and powerful Neural Network Library for Python

Neurolab Neurolab is a simple and powerful Neural Network Library for Python. Contains based neural networks, train algorithms and flexible framework

152 Dec 06, 2022
3rd place solution for the Weather4cast 2021 Stage 1 Challenge

weather4cast2021_Stage1 3rd place solution for the Weather4cast 2021 Stage 1 Challenge Dependencies The code can be executed from a fresh environment

5 Aug 14, 2022
Semantically Contrastive Learning for Low-light Image Enhancement

Semantically Contrastive Learning for Low-light Image Enhancement Here, we propose an effective semantically contrastive learning paradigm for Low-lig

48 Dec 16, 2022
Low-dose Digital Mammography with Deep Learning

Impact of loss functions on the performance of a deep neural network designed to restore low-dose digital mammography ====== This repository contains

WANG-AXIS 6 Dec 13, 2022
This repository contains the accompanying code for Deep Virtual Markers for Articulated 3D Shapes, ICCV'21

Deep Virtual Markers This repository contains the accompanying code for Deep Virtual Markers for Articulated 3D Shapes, ICCV'21 Getting Started Get sa

KimHyomin 45 Oct 07, 2022
Towards Rolling Shutter Correction and Deblurring in Dynamic Scenes (CVPR2021)

RSCD (BS-RSCD & JCD) Towards Rolling Shutter Correction and Deblurring in Dynamic Scenes (CVPR2021) by Zhihang Zhong, Yinqiang Zheng, Imari Sato We co

81 Dec 15, 2022
"Domain Adaptive Semantic Segmentation without Source Data" (ACM MM 2021)

LDBE Pytorch implementation for two papers (the paper will be released soon): "Domain Adaptive Semantic Segmentation without Source Data", ACM MM2021.

benfour 16 Sep 28, 2022
Fine-tune pretrained Convolutional Neural Networks with PyTorch

Fine-tune pretrained Convolutional Neural Networks with PyTorch. Features Gives access to the most popular CNN architectures pretrained on ImageNet. A

Alex Parinov 694 Nov 23, 2022
Code for "SRHEN: Stepwise-Refining Homography Estimation Network via Parsing Geometric Correspondences in Deep Latent Space"

SRHEN This is a better and simpler implementation for "SRHEN: Stepwise-Refining Homography Estimation Network via Parsing Geometric Correspondences in

1 Oct 28, 2022
PyTorch implementation of PSPNet segmentation network

pspnet-pytorch PyTorch implementation of PSPNet segmentation network Original paper Pyramid Scene Parsing Network Details This is a slightly different

Roman Trusov 532 Dec 29, 2022
University of Rochester 2021 Summer REU focusing on music sentiment transfer using CycleGAN

Music-Sentiment-Transfer University of Rochester 2021 Summer REU focusing on music sentiment transfer using CycleGAN Poster: Music Sentiment Transfer

Miles Sigel 2 Jan 24, 2022
[ArXiv 2021] One-Shot Generative Domain Adaptation

GenDA - One-Shot Generative Domain Adaptation One-Shot Generative Domain Adaptation Ceyuan Yang*, Yujun Shen*, Zhiyi Zhang, Yinghao Xu, Jiapeng Zhu, Z

GenForce: May Generative Force Be with You 46 Dec 19, 2022
A large-image collection explorer and fast classification tool

IMAX: Interactive Multi-image Analysis eXplorer This is an interactive tool for visualize and classify multiple images at a time. It written in Python

Matias Carrasco Kind 23 Dec 16, 2022
Code release for "BoxeR: Box-Attention for 2D and 3D Transformers"

BoxeR By Duy-Kien Nguyen, Jihong Ju, Olaf Booij, Martin R. Oswald, Cees Snoek. This repository is an official implementation of the paper BoxeR: Box-A

Nguyen Duy Kien 111 Dec 07, 2022
ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator

ONNX Runtime is a cross-platform inference and training machine-learning accelerator. ONNX Runtime inference can enable faster customer experiences an

Microsoft 8k Jan 04, 2023