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A semi-supervised online video object segmentation algorithm, which accepts user annotations about a target object at the first frame, is proposed in this work. We propagate the segmentation labels at the previous frame to the current frame using optical flow vectors. However, the propagation is error-prone. Therefore, we develop the convolutional trident network (CTN), which has three decoding branches: separative, definite foreground, and definite background decoders. Then, we perform Markovdoi:10.1109/cvpr.2017.790 dblp:conf/cvpr/JangK17 fatcat:hjgqlh6f3vglhcijywcqwagk4m