Constrained parametric min-cuts for automatic object segmentation

We present a novel framework for generating and ranking plausible objects hypotheses in an image using bottom-up processes and mid-level cues. The object hypotheses are represented as figure-ground segmentations, and are extracted automatically, without prior knowledge about properties of individual...

Ausführliche Beschreibung

Bibliographische Detailangaben

Hauptverfasser:	Carreira, Joao, Sminchisescu, Cristian
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Computer vision Humans Image segmentation Machine learning Machine learning algorithms Mathematics Numerical simulation Object segmentation Predictive models
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