CompenHR

Introduction

This is PyTorch implementation of the paper“CompenHR: Efficient Full Compensation for High-resolution Projector”.

@inproceedings{wang2023compenhd,
    author = {Yuxi Wang and Bingyao Huang and Haibin Ling},
    title = {CompenHR: Efficient Full Compensation for High-resolution Projector},
    booktitle = {IEEE Virtual Reality and 3D User Interfaces (VR)},
    month = {April},
    year = {2023} }

Datasets

The high resolution compensation datasets:

lavender, bubble, cube, cloud, stripes, water, train,test,ref.

leaf_np, lemon_np, flower_np, rock_np, stripes_np.

Usage

1. Clone this repo:

 git clone https://github.com/cyxwang/CompenHR
 
 cd CompenHR/src/python

2. Download dataset and extract to ‘data/’

3. Start visdom by typing:

 visdom

4. Run train_CompenHR.py to produce results:

 python train_CompenHR.py