VCAS-Motion (Video Class Agnostic Segmentation Benchmark)
Introduced by Siam et al. in Video Class Agnostic Segmentation Benchmark for Autonomous Driving
Video class agnostic segmentation (VCAS) is the task of segmenting objects without regards to its semantics combining appearance, motion and geometry from monocular video sequences. The main motivation behind this is to account for unknown objects in the scene and to act as a redundant signal along with the segmentation of known classes for better safety as shown in the following Figure.
This VCAS benchmark is built from KITTI-MOTS and Cityscapes-VPS.
Papers
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