Recurrent Convolutional Neural Networks for Scene Parsing

Understand

Scene parsing is a technique that consist on giving a label to all pixels in an image according to the class they belong to.

• To ensure a good visual coherence and a high class accuracy, it is essential for a scene parser to capture image long range dependencies.
• In a feed-forward architecture, this can be simply achieved by considering a sufficiently large input context patch, around each pixel to be labeled.
• We propose an approach consisting of a recurrent convolutional neural network which allows us to consider a large input context, while limiting the capacity of the model.