High-qualitypixel-level annotation is still time-consuming and laborious — a bottleneck for several deep learning applications . Weshow that our approach can surpass the accuracy of state-of-the-art methods in .ground segmentation datasets: iCoSeg, DAVIS, and Rooftop . It achieves 91.5\% accuracy in a known semantic segmentation dataset, Cityscapes, being 74.75 times faster than the original annotation procedure . The appendixpresents additional qualitative results . Code and video demonstration will be released upon publication . The

Author(s) : Jordão Bragantini, Alexandre Falcão, Laurent Najman

Links : PDF - Abstract

Code :
Coursera

Keywords : annotation - segmentation - accuracy - - qualitative -

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