ActiveStereoNet

This repository builds upon the open source pytorch Active stereo net implementation and extends it to active tartanair and D435i datsets.

Paper

ActiveStereoNet: End-to-End Self-Supervised Learning for Active Stereo Systems

Requirments

CUDA = v11.1

CuDNN >= v8.2.1

Python > 3.8

Pytorch

Torchvision

Dataset

Datasets used:

1. D435i dataset (real data)
2. Active TartanAir dataset (virtual data)

Please, use the links provided to download the datasets and update the data_root field in the Options/*.json files.

Usage

To train on D435i sequences:

sh d435i.sh

To train on Active Tartanair sequences:

sh tartanair.sh