Datasets › ConsInv Dataset

ConsInv Dataset

Introduced by Adrian Bojko et al. in Self-Improving SLAM in Dynamic Environments: Learning When to Mask15 Oct 2022 archive 2025-07-28

ConsInv is a stereo RGB + IMU dataset designed for Dynamic SLAM testing and contains two subsets:

  • ConsInv-Indoors contains sequences in an office setting where small objects are moved.
  • ConsInv-Outdoors contains sequences in an urban environment, where cars and/or people move.

The novelty of ConsInv dataset is 1) the controlled degree of difficulty, from easy to very hard, and 2) the fact that the difficulty of the sequences comes only from object motion: relative motion between camera and object, motion ambiguity, challenging points of view when objects move. The difficulty does not come from motion speed, lack of features, lens flare, etc. - typically seen in other SLAM datasets.

Benchmarks archive 2025-07-28

No leaderboard in the archive resolves to this dataset.

Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 1 paper for it but never published that list.

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

No licence recorded in the archive. Absence here is not a statement about the dataset's terms.

Modalities archive 2025-07-28

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

  • ConsInv Dataset

1 variant name, as the archive lists them.

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