Azeez Oluwafemi, Yang Zou, B. V. K. Vijaya Kumar
Published 2019-10-23Version 1
Monocular Depth Estimation is usually treated as a supervised and regression problem when it actually is very similar to semantic segmentation task since they both are fundamentally pixel-level classification tasks. We applied depth increments that increases with depth in discretizing depth values and then applied Deeplab v2 and the result was higher accuracy. We were able to achieve a state-of-the-art result on the KITTI dataset and outperformed existing architecture by an 8% margin.
On Monocular Depth Estimation and Uncertainty Quantification using Classification Approaches for Regression
Monocular Depth Estimation with Directional Consistency by Deep Networks
Monocular Depth Estimation via Listwise Ranking using the Plackett-Luce model
![QR code for arXiv:1910.10369 [cs.CV]](http://oss.arxitics.com/images/favicon.svg)