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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

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Active stereo net implementation for active tartanair and D435i datsets

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