An Adversarial Generative Network Designed for High-Resolution Monocular Depth Estimation from 2D HiRISE Images of Mars

1 code implementation • Remote Sensing 2022 • Riccardo La Grassa, Ignazio Gallo, Cristina Re, Gabriele Cremonese, Nicola Landro, Claudio Pernechele, Emanuele Simioni, Mattia Gatti

In this paper, we combine these last two concepts into a single end-to-end model and introduce a new generative adversarial network solution that estimates the DTM at 4× resolution from a single monocular image, called SRDiNet (super-resolution depth image network).

Generative Adversarial Network Monocular Depth Estimation +2