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The reconstruction of the depth from a single image has been a difficult task due to the complexity and the amount of depth indications that a single image can contain. Convolutional Neural Networks (RNC) have been used successfully to reconstruct the depth of objects in general scenes; however, these works have not been adapted for the particular problem of depth reconstruction from perspective. Our proposal is based on building an efficient computational RNC; we focus on Completely Convolutional Neural Networks (RNCC), whose training requires a single stage. We compared our RNC with the current state of the art in depth reconstruction, obtaining improvements in global levels for road images with present perspective.

Reconstrucción de profundidad a partir de una sola imagen con perspectiva mediante redes neuronales completamente convolucionales