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Diagnose_VLN

This repository contains the code and data for our paper: Diagnosing Vision-and-language Navigation: What Really Matters.

Directory Structure

We cover three VLN datasets and nine agents in our study.

Installation

git clone --recursive https://github.com/VegB/Diagnose_VLN

We describe the detailed environment setup for each model in the corresponding directory. For instance, guidance to setup R2R-EnvDrop can be found here.

Data Preparation

  • Prepare R2R data: link
  • Prepare RxR data: link
  • Prepare Touchdown data: link

Acknowledgements

We thank the authors for Matterport3DSimulator, R2R-EnvDrop, FAST, Recurrent-VLN-BERT, PREVALENT_R2R, CLIP-ViL-VLN, VLN-HAMT, RCONCAT, ARC, VLN-Transformer for sharing their code!