This repository contains:
- a PyTorch data loader for Spring, see
dataloader.py
- code to convert Spring data into point clouds, see
pointcloud.py
- code to convert Spring disparity maps into metric depth maps, see
get_depth
inpointcloud.py
Required python libraries:
- flow_library (for reading/writing flow/disparity files)
- open3d (for 3d point cloud visualization)
- pytorch (for dataloader)
If you make use of this code, please cite our paper:
@InProceedings{Mehl2023_Spring,
author = {Lukas Mehl and Jenny Schmalfuss and Azin Jahedi and Yaroslava Nalivayko and Andr\'es Bruhn},
title = {Spring: A High-Resolution High-Detail Dataset and Benchmark for Scene Flow, Optical Flow and Stereo},
booktitle = {Proc. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2023}
}