High-fidelity wheat plant reconstruction using 3D Gaussian splatting and neural radiance fields
We believe that these new methods will be transformative in the field of 3D plant phenotyping, plant reconstruction, and active vision. To further this cause, we release all robot configuration and control software, alongside our extensive multiview dataset. We also release all scripts necessary to train both 3DGS and NeRF, all trained models data, and final 3D point cloud representations. Our dataset can be accessed via https://plantimages.nottingham.ac.uk/ or https://https://doi.org/10.5524/102661. Our software can be accessed via https://github.com/Lewis-Stuart-11/3D-Plant-View-Synthesis.
Authors
- Jonathan A. Atkinson (ORCID: https://orcid.org/0000-0003-2815-0812)
- Michael P. Pound (ORCID: https://orcid.org/0000-0002-5016-1078)
- Darren M. Wells (ORCID: https://orcid.org/0000-0002-4246-4909)
- Jack Walker
- Simon Castle-Green (ORCID: https://orcid.org/0000-0003-0681-2555)
- Lewis A G Stuart
Institutions
- University of Nottingham (GB)
Publication Details
- Journal
- GigaScience
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1093/gigascience/giaf022
- Citations
- 15
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 26.25
Funders
- University of Nottingham