Constrained Parametric MinCuts for Automatic Object Segm entation Joao Carreira and Cristian Sminchisescu Computer Vision and Machine Learning Group Institute for N umerical Simulation Faculty of Math
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Constrained Parametric MinCuts for Automatic Object Segm entation Joao Carreira and Cristian Sminchisescu Computer Vision and Machine Learning Group Institute for N umerical Simulation Faculty of Math

sminchisescu insunibonnde Abstract We present a novel framework for generating and rank ing plausible objects hypotheses in an image using bottom up processes and midlevel cues The object hypotheses are represented as 64257gureground segmentations an

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Constrained Parametric MinCuts for Automatic Object Segm entation Joao Carreira and Cristian Sminchisescu Computer Vision and Machine Learning Group Institute for N umerical Simulation Faculty of Math




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Presentation on theme: "Constrained Parametric MinCuts for Automatic Object Segm entation Joao Carreira and Cristian Sminchisescu Computer Vision and Machine Learning Group Institute for N umerical Simulation Faculty of Math"— Presentation transcript: