Improve segmentation of close objects in video using optical flow with BATMAN
Improve segmentation of close objects in video using optical flow with BATMAN
BATMAN: Bilateral Attention Transformer in Motion-Appearance Neighboring Space for Video Object Segmentation
arXiv paper abstract https://arxiv.org/abs/2208.01159
arXiv PDF paper https://arxiv.org/pdf/2208.01159.pdf
Video Object Segmentation (VOS) is fundamental to video understanding.
... existing work faces challenges segmenting visually similar objects in close proximity of each other.
... propose a novel Bilateral Attention Transformer in Motion-Appearance Neighboring space (BATMAN) for semi-supervised VOS.
It captures object motion in the video via a novel optical flow calibration module that fuses the segmentation mask with optical flow estimation to improve within-object optical flow smoothness and reduce noise at object boundaries.
... employed ... novel bilateral attention, which computes the correspondence between the query and reference frames in the neighboring bilateral space considering both motion and appearance.
... BATMAN ... outperforming all existing state-of-the-art on all four popular VOS benchmarks ...
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