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CNN in MRF: Video Object Segmentation via Inference in a CNN-Based Higher-Order Spatio-Temporal MRF
2018
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition
This paper addresses the problem of video object segmentation, where the initial object mask is given in the first frame of an input video. We propose a novel spatiotemporal Markov Random Field (MRF) model defined over pixels to handle this problem. Unlike conventional MRF models, the spatial dependencies among pixels in our model are encoded by a Convolutional Neural Network (CNN). Specifically, for a given object, the probability of a labeling to a set of spatially neighboring pixels can be
doi:10.1109/cvpr.2018.00626
dblp:conf/cvpr/BaoW018
fatcat:xneli3oh2fek7phgiouhbi2a2m