3DCotton

Authors

Md Ahmed Al Muzaddid, University of Texas at Arlington
William J. Beksi, University of Texas at Arlington

ORCID Identifier(s)

ORCID 0000-0002-7916-714X, ORCID 0000-0001-5377-2627

Document Type

Dataset

Source Publication Title

CropNeRF: A Neural Radiance Field-Based Framework for Crop Counting

DOI

https://doi.org/10.32855/dataset.2026.02.042

Related Publication(s)

Muzaddid, M. A. A., and Beksi, W. J. (2026). CropNeRF: A Neural Radiance Field-Based Framework for Crop Counting. arXiv preprint arXiv:2601.00207.

Production/Collection Date

2024

Production/Collection Location

College Station, TX, USA

Depositor

William J. Beksi

Deposit Date

2-7-2026

Data Type

Image

Abstract

3DCotton is an image dataset consisting of 8 cotton plants recorded at the Texas A&M University Research Farm. The images were captured using an Apple iPhone at a resolution of 1040x1920 pixels. Approximately 150 images per plant were taken from a distance of 1 m by recording multiple viewpoints. These images can be utilized for developing 3D reconstruction methods.

Disciplines

Agriculture | Artificial Intelligence and Robotics

Publication Date

6-1-2026

Language

English

Comments

Project website: https://robotic-vision-lab.github.io/cropnerf

License

This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.

Recommended Citation

Muzaddid, Md Ahmed Al and Beksi, William J., "3DCotton" (2026). Agriculture. 1.
https://mavmatrix.uta.edu/rvl_agri_datasets/1