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Oriented Object Detection datasets

archive 2025-07-28

5 datasets carry the task tag "Oriented Object Detection" (the task itself: Oriented Object Detection), ordered by the archive's paper count. Page 1 of 1: 5 shown of 5. Facet routes are this site's own (the archive records the tag string, not a page).

The archive holds 12,214 dataset rows; 12,172 are listed. 6 are withheld from every listing and count here as vandalised before snapshot (6 with contact-centre spam in the title, 0 with a spam description on a row that has no homepage, no paper and no papers counted; none with more than 1 paper, 0 with a benchmark), listed in withheld.json; 1 listed row carries a vandalised description, withheld on its page. This gate never withholds a row with a homepage or a paper that resolves, and a clean description; the content rules below withhold a row whose name is spam whatever else it carries. The gate is a phrase list: these are the rows it caught, not a claim that the rest is clean. Before that gate, the site's content rules withhold 36 more rows (invite-code, gambling, travel-booking, contact-centre and similar spam in the name or on a row with nothing real behind it); they have no page and are listed in withheld.json.

Filter 51 task tags shown of 3,717, by dataset count; the full filter by modality, task and language is on /datasets

Oriented Object Detection datasets 1–5 of 5

DOTA (Dataset for Object deTection in Aerial Images)
DOTA is a large-scale dataset for object detection in aerial images.
293 papers · 2 benchmarks
DOTA 2.0 (Dataset of Object deTection in Aerial images)
—In the past decade, object detection has achieved significant progress in natural images but not in aerial images, due to the massive variations in the scale and orientation of objects caused by the bird’s-eye view of aerial images.
10 papers · 0 benchmarks
SODA-A is a large-scale benchmark specialized for small object detection task under aerial scenes, which has 800203 instances with oriented rectangle box annotation across 9 classes.
7 papers · 0 benchmarks
VD4UAV is an altitude-sensitive benchmark dataset designed to evade vehicle detection in Unmanned Aerial Vehicle (UAV) imagery.
2 papers · 2 benchmarks
The TimberVision dataset consists of more than 2k annotated RGB images and contains a total of 51k trunk components including cut and lateral surfaces, thereby surpassing any existing dataset in this domain in terms of both quantity and…
1 paper · 0 benchmarks

Paper counts and descriptions are the archive's, frozen 2025-07-28; no citation counts, no stars, no trending. Sorting by "most cited" or "newest" was a live-site feature the archive does not carry.