computer-vision-6
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.
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Benchmarks
These leaderboards are used to track progress in video-instance-segmentation-6
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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-6 models and implementations
3 papers 399
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Most implemented papers
Simple online and realtime tracking with a deep association metric
D. Paulus, N. Wojke, Alex Bewley•Mon Mar 20 2017
This paper integrates appearance information to improve the performance of SORT and reduces the number of identity switches, achieving overall competitive performance at high frame rates.
4261
