Super Resolution Depth Maps

Supervision: Christian Rupprecht, Federico Tombari

This project aims at single image super-resolution applied to depth maps. Many available depth sensors have a relatively low resolution compared to the accompanied color image. We would like to recover a high-resolution depth map from the combination of low-res depth and high-res RGB image. This problem is inherently ill-posed since a multiplicity of solutions exist for any given input. Nonetheless it is a highly studies topic in computer vision. Starting with the work of Dong et. al. "Image Super-Resolution Using Deep Convolutional Networks" (TPAMI 2015) we would like to expore the application of deep neural networks to this field of study.

For further information please contact: Christian Rupprecht