We propose a method that can generate highly detailed high-resolution depth estimations from a single image. Our method is based on optimizing the performance of a pre-trained network by merging estimations in different resolutions and different patches to generate a high-resolution estimate. Abstract Neural networks have shown great abilities in estimating depth from a single image. However, the
![Boosting Monocular Depth Estimation Models to High-Resolution via Content-Adaptive Multi-Resolution Merging](https://cdn-ak-scissors.b.st-hatena.com/image/square/0194274da87d7b2a472c20ee65a37cf6c0e380c8/height=288;version=1;width=512/https%3A%2F%2Fyaksoy.github.io%2Fimages%2FhrdepthTeaser.jpg)