Description. Python support library for using the NYU Depth Dataset V2. The official toolbox for processing the raw dataset is written in MATLAB. This ...

PyTorch wrapper for the NYUv2 dataset focused on multi-task learning. Data sources available: RGB, Semantic Segmentation(13), Surface Normals, Depth Images.

The NYU-Depth V2 data set is comprised of video sequences from a variety of indoor scenes as recorded by both the RGB and Depth cameras from the Microsoft ...

This is a model for monocular depth estimation trained on the NYU Depth V2 dataset, as described in the paper Deeper Depth Prediction with Fully ...

NYU Depth V2 Tools for Evaluating Superpixel Algorithms. This repository contains several tools to pre-process the ground truth segmentations as provided by the ...

[CVPR 2021] Monocular depth estimation using wavelets for efficiency - wavelet-monodepth/NYUv2/README.md at main · nianticlabs/wavelet-monodepth.

This repository contains 13 class labels for both train and test dataset in NYUv2. This is to avoid any hassle involved in parsing the data from the .mat ...

When we apply monocular depth estimation on NYU-d v2 dataset, we shoule generate the RGB image and dense depth map ourself, the process method is as follows.