Journal
COMPUTATIONAL VISUAL MEDIA
Volume 6, Issue 1, Pages 65-78Publisher
SPRINGERNATURE
DOI: 10.1007/s41095-020-0156-x
Keywords
video segmentation; water segmentation; appearance adaptation
Categories
Funding
- National Science Foundation [EAR 1760582]
- Louisiana Board of Regents ITRS [LEQSF(2018-21)-RD-B-03]
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We develop a novel network to segment water with significant appearance variation in videos. Unlike existing state-of-the-art video segmentation approaches that use a pre-trained feature recognition network and several previous frames to guide segmentation, we accommodate the object's appearance variation by considering features observed from the current frame. When dealing with segmentation of objects such as water, whose appearance is non-uniform and changing dynamically, our pipeline can produce more reliable and accurate segmentation results than existing algorithms.
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