/lamar-benchmark

Source code for the ECCV 2022 paper "Benchmarking Localization and Mapping for Augmented Reality".

Primary LanguagePythonCreative Commons Attribution 4.0 InternationalCC-BY-4.0


LaMAR
Benchmarking Localization and Mapping
for Augmented Reality

Paul-Edouard Sarlin* · Mihai Dusmanu*
Johannes L. Schönberger · Pablo Speciale · Lukas Gruber · Viktor Larsson · Ondrej Miksik · Marc Pollefeys

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ECCV 2022

Project Page | Video

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LaMar includes multi-sensor streams recorded by AR devices along hundreds of unconstrained trajectories
captured over 2 years in 3 large indoor+outdoor locations.

This repository hosts the source code for LaMAR, a new benchmark for localization and mapping with AR devices in realistic conditions. We are still in the process of fully releasing the benchmark. Here is the release plan:

  • Evaluation data: apply here
  • Evaluation, baselines, data format: see below
  • Additional documentation
  • Ground truthing pipeline: to be released soon
  • Full raw data: to be released soon
  • Leaderboard and evaluation server

Running the evaluation

Requirements:

  • Python >= 3.8
  • pycolmap installed from source (recommended) or via pip install pycolmap
  • hloc and its dependencies
  • raybender
  • pyceres
  • everything listed in requirements.txt, via python -m pip install -r requirements.txt

Running the single-frame evaluation:

python -m lamar_benchmark.run \
	--scene SCENE --ref_id map --query_id query_phone \
	--retrieval netvlad --feature sift --matcher mnn

By default, the script assumes that the data was placed in ./data/ and will write the intermediate dumps and final outputs to ./outputs/.

BibTex citation

Please consider citing our work if you use any code from this repo or ideas presented in the paper:

@inproceedings{sarlin2022lamar,
  author    = {Paul-Edouard Sarlin and
               Mihai Dusmanu and
               Johannes L. Schönberger and
               Pablo Speciale and
               Lukas Gruber and
               Viktor Larsson and
               Ondrej Miksik and
               Marc Pollefeys},
  title     = {{LaMAR: Benchmarking Localization and Mapping for Augmented Reality}},
  booktitle = {ECCV},
  year      = {2022},
}

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