Skip to content

DK05310214/What-have-the-Single-Image-Based-Depth-Estimation-Models-Learnt

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

3 Commits
 
 
 
 
 
 

Repository files navigation

What have the Single Image Based Depth Estimation Models Learnt?

This repository contains experimental data pertaining to two key areas of research in computer vision and depth estimation. Below, you will find a brief overview of the contents and instructions on how to properly cite this work if you plan to use the data provided.

Contents

The repository is organized into two main sections:

  1. Texture-less Region and Surroundings Depth Overlap Index: This section includes experimental data related to the overlap index of estimated depth in areas lacking texture and their immediate surroundings. The data is crucial for understanding how depth estimation models perform in regions where texture information is minimal or absent.

  2. Visual Salience and Depth Estimation Error Relationship: This section houses experimental data on the relationship between visual saliency and the errors in depth estimation. This data aids in analyzing how the prominence of visual elements in a scene can affect the accuracy of depth predictions.

Data Usage

If you wish to use the data provided in this repository for your research, please ensure to cite our work appropriately.

Citation

To cite this work, please use the following reference:

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published