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The 1st Tiny Object Detection Challenge:Methods and Results

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arxiv 2009.07506 v2 pith:Z4EQSCEZ submitted 2020-09-16 cs.CV

classification cs.CV
keywords challengedetectiontinymethodsobjectbriefdatasetimages
verification ladder T0 review T1 audit T2 compute T3 formal
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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.

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