Datasets › YouTube-VIS 2019
YouTube-VIS 2019
YouTubeVIS is a new dataset tailored for tasks like simultaneous detection, segmentation and tracking of object instances in videos and is collected based on the current largest video object segmentation dataset YouTubeVOS.
Source: YouTubeVIS
Benchmarks archive 2025-07-28
All 2 leaderboards whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.
| First row (archive order) | Paper | Code | ||||
|---|---|---|---|---|---|---|
| Video Instance Segmentation | YouTube-VIS validation | CAVIS(ViT-L, Online) mask AP 68.9 | Context-Aware Video Instance Segmentation | Seung-Hun-Lee/CAVIS | 44 | Compare |
| Video Instance Segmentation | YouTube-VIS | Temporal ROI Align mask AP 38 | Temporal RoI Align for Video Object Recognition | open-mmlab/mmtracking | 1 | Compare |
Papers archive 2025-07-28
30 shown of 34 papers with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 163. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.
The full list of 34 is in the JSON twin.
Dataset loaders archive 2025-07-28
2 loaders as listed in the archive; links are outbound and not re-checked here.
Tasks archive 2025-07-28
License archive 2025-07-28
Modalities archive 2025-07-28
Languages archive 2025-07-28
No language tagged.
Variants archive 2025-07-28
- YouTube-VIS
- YouTube-VIS validation
- YouTube-VIS 2019
3 variant names, as the archive lists them.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections