mlsanityData to 7 Oct 2026

The 1st Tiny Object Detection Challenge:Methods and Results

arXiv 2009.07506 ↗First posted 16 Sep 2020cs.CVcited by 14

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Abstract (arXiv)

The 1st Tiny Object Detection (TOD) Challenge aims to encourage research in developing novel and accurate methods for tiny object detection in images which have wide views, with a current focus on tiny person detection. The TinyPerson dataset was used for the TOD Challenge and is publicly released. It has 1610 images and 72651 box-levelannotations. Around 36 participating teams from the globe competed inthe 1st TOD Challenge. In this paper, we provide a brief summary of the1st TOD Challenge including brief introductions to the top three methods.The submission leaderboard will be reopened for researchers that areinterested in the TOD challenge. The benchmark dataset and other information can be found at: https://github.com/ucas-vg/TinyBenchmark.

Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). First posted on arXiv 16 Sep 2020.

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Citing papers per year: 2021: 4; 2022: 2; 2023: 2; 2024: 2; 2025: 4.

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