Learning to Zoom: a Saliency-Based Sampling Layer for Neural Networks

ECCV 2018 Adrià RecasensPetr KellnhoferSimon StentWojciech MatusikAntonio Torralba

We introduce a saliency-based distortion layer for convolutional neural networks that helps to improve the spatial sampling of input data for a given task. Our differentiable layer can be added as a preprocessing block to existing task networks and trained altogether in an end-to-end fashion... (read more)

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