Contribution to Panoptic Segmentation
Contribution au Segmentation Panoptique
Résumé
Full visual scene understanding has always been one of the main goals of machine perception. The ability to describe the components of a scene using only information taken by a digital camera has been the main focus of computer vision tasks such as semantic segmentation and instance segmentation. Where by using Deep Learning techniques, a neural network is capable to assign a label to each pixel of an image (semantic segmentation) or define the boundaries of an instance or object with more precision than a bounding box (instance segmentation).
The task of Panoptic Segmentation tries to achieve a full scene description by merging semantic and instance segmentation information and leveraging the strengths of these two tasks. On this report it is shown a possible alternative to solve this merging problem by using Convolutional Neural Networks (CNNs) to refine the boundaries between each class.
Origine : Fichiers produits par l'(les) auteur(s)
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