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Real-time Instance Segmentation datasets

archive 2025-07-28

6 datasets carry the task tag "Real-time Instance Segmentation" (the task itself: Real-time Instance Segmentation), ordered by the archive's paper count. Page 1 of 1: 6 shown of 6. 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

Real-time Instance Segmentation datasets 1–6 of 6

The COCO (Common Objects in Context) dataset is a large-scale object detection, segmentation, and captioning dataset.
11,922 papers · 77 benchmarks
Cityscapes is a large-scale database which focuses on semantic understanding of urban street scenes.
3,702 papers · 51 benchmarks
KITTI (Karlsruhe Institute of Technology and Toyota Technological Institute) is one of the most popular datasets for use in mobile robotics and autonomous driving.
3,661 papers · 137 benchmarks
Multi30K is a large-scale multilingual multimodal dataset for interdisciplinary machine learning research.
139 papers · 2 benchmarks
Click to add a brief description of the dataset (Markdown and LaTeX enabled).
90 papers · 13 benchmarks
MEIS (M-mode Echocardiograms for Instance Segmentation)
MEIS comprises a total of 2,639 images in the size of 1024 × 768 toward two recording views (Aortic Valve (AV) and Left Ventricle (LV)) with 1,521 (747 in AV + 774 in LV) images for training and 1,118 (559 in AV + 559 in LV) for testing,…
1 paper · 1 benchmark

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.