mlsanityData to 7 Oct 2026

The Robotic Vision Scene Understanding Challenge

arXiv 2009.05246 ↗First posted 11 Sep 2020cs.ROcited by 9

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Abstract (arXiv)

Being able to explore an environment and understand the location and type of all objects therein is important for indoor robotic platforms that must interact closely with humans. However, it is difficult to evaluate progress in this area due to a lack of standardized testing which is limited due to the need for active robot agency and perfect object ground-truth. To help provide a standard for testing scene understanding systems, we present a new robot vision scene understanding challenge using simulation to enable repeatable experiments with active robot agency. We provide two challenging task types, three difficulty levels, five simulated environments and a new evaluation measure for evaluating 3D cuboid object maps. Our aim is to drive state-of-the-art research in scene understanding through enabling evaluation and comparison of active robotic vision systems.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). First posted on arXiv 11 Sep 2020.

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Citing papers per year: 2021: 2; 2022: 1; 2023: 2; 2024: 2; 2025: 2.

9 papers.