computer-vision-20
Video Instance Segmentation
3260 papers • 126 benchmarks • 313 datasets
The goal of video instance segmentation is simultaneous detection, segmentation and tracking of instances in videos. In words, it is the first time that the image instance segmentation problem is extended to the video domain. To facilitate research on this new task, a large-scale benchmark called YouTube-VIS, which consists of 2,883 high-resolution YouTube videos, a 40-category label set and 131k high-quality instance masks is built.
(Image credit: Open Source)
Benchmarks
These leaderboards are used to track progress in video-instance-segmentation-20
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YouTube-VIS validation
YouTube-VIS validation
OVIS validation
OVIS validation
YouTube-VIS 2021
Libraries
iUse these libraries to find video-instance-segmentation-20 models and implementations
3 papers 399
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