High-fidelity wheat plant reconstruction using 3D Gaussian splatting and neural radiance fields.

ABSTRACT:

Background

The reconstruction of 3-dimensional (3D) plant models can offer advantages over traditional 2-dimensional approaches by more accurately capturing the complex structure and characteristics of different crops. Conventional 3D reconstruction techniques often produce sparse or noisy representations of plants using software or are expensive to capture in hardware. Recently, view synthesis models have been developed that can generate detailed 3D scenes, and even 3D models, from only RGB images and camera poses. These models offer unparalleled accuracy but are currently data hungry, requiring large numbers of views with very accurate camera calibration.

Results

In this study, we present a view synthesis dataset comprising 20 individual wheat plants captured across 6 diff

SUBMITTER: Stuart LAG 

PROVIDER: S-EPMC11945317 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature