LGDWT-GS

Local and Global Discrete Wavelet-Regularized 3D Gaussian Splatting
for Sparse-View Scene Reconstruction

Shima Salehi Atharva Agashe Andrew J. McFarland Joshua Peeples
Texas A&M University

Qualitative Comparison

Results on MipNeRF360 and LLFF datasets. Side-by-side comparison of LGDWT-GS (ours) vs 3DGS demonstrating improved detail preservation and sharper reconstructions with our method.

Bicycle / MipNeRF360

3DGS Bicycle
3DGS
LGDWT-GS Bicycle
LGDWT-GS (Ours)

Flower / LLFF

3DGS Flower
3DGS
LGDWT-GS Flower
LGDWT-GS (Ours)

Abstract & Method

We propose a new method for few-shot 3D reconstruction that integrates global and local frequency regularization to stabilize geometry and preserve fine details under sparse-view conditions, addressing a key limitation of existing 3D Gaussian Splatting (3DGS) models. We also introduce a new multispectral greenhouse dataset containing four spectral bands captured from diverse plant species under controlled conditions. Alongside the dataset, we release an open-source benchmarking package that defines standardized few-shot reconstruction protocols for evaluating 3DGS-based methods. Experiments on our multispectral dataset, as well as standard benchmarks, demonstrate that the proposed method achieves sharper, more stable, and spectrally consistent reconstructions than existing baselines.

Method Pipeline

Package

We release an open-source benchmarking package that defines standardized few-shot reconstruction protocols for evaluating 3DGS-based methods. The package provides comprehensive evaluation tools and metrics for sparse-view 3D reconstruction tasks.

Benchmarking Package

Multispectral Greenhouse Dataset

We introduce a new multispectral greenhouse dataset containing four spectral bands. The dataset includes multiple plant species (sorghum, tomato, alocasia, cotton, grape) captured under controlled greenhouse conditions.

580 nm (Green)

Green Channel 580nm

660 nm (Red)

Red Channel 660nm

735 nm (Red Edge)

Red Edge Channel 735nm

820 nm (NIR)

NIR Channel 820nm

Pseudo RGB

Pseudo RGB

Citation

@article{salehi2024lgdwtgs,
  title={LGDWT-GS: Local and Global Discrete Wavelet-Regularized 3D Gaussian Splatting for Sparse-View Scene Reconstruction},
  author={Salehi, Shima and Agashe, Atharva and McFarland, Andrew J. and Peeples, Joshua},
  journal={arXiv preprint arXiv:2601.17185},
  year={2026}
}

Acknowledgments

This material is based upon work supported by the Texas A&M University System Nuclear Security Office. Portions of this research were conducted with the advanced computing resources provided by Texas A&M High Performance Research Computing.