Super-resolution of interpolated downsampled semi-dense depth map

P. 1–2.

Makarov I., Alisa Korinevskaya, Vladimir Aliev

We study depth map reconstruction for a specific task of fast rough depth approximation having sparse depth samples obtained from low-cost depth sensors or SLAM algorithms. We propose a model interpolating downsampled semi-dense depth values and then processing super-resolution. We study our method in comparison with the state-of-the-art approaches transferring RGB information to depth. It appears that the proposed approach can be used to approximately estimate high-resolution depth maps.

Keywords: depth interpolation, depth super-resolution

Publication based on the results of: Applied network research with big data and new technological advances (2018)

In book

Proceedings of the 23rd International ACM Conference on 3D Web Technology

NY: Association for Computing Machinery (ACM), 2018.