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This paper introduces a novel contour-based approach named deep snake for real-time instance segmentation. Unlike some recent methods that directly regress the coordinates of the object boundary points from an image, deep snake uses a neural network to iteratively deform an initial contour to match the object boundary, which implements the classic idea of snake algorithms with a learning-based approach. For structured feature learning on the contour, we propose to use circular convolution indoi:10.1109/cvpr42600.2020.00856 dblp:conf/cvpr/PengJPLBZ20 fatcat:ubz3m3a3rfcpjlbuzn4mticnl4