LEGS improves 3D Gaussian Splatting by replacing first-order edge guidance with second-order Laplacian structural guidance and nonlinear pixel-wise weighting, yielding up to 1.68 dB PSNR gain over baseline 3DGS on Tanks&Temples and Mip-NeRF360.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
LEGS: Laplacian-Enhanced Gaussian Splatting with a Nonlinear Weighted Loss
LEGS improves 3D Gaussian Splatting by replacing first-order edge guidance with second-order Laplacian structural guidance and nonlinear pixel-wise weighting, yielding up to 1.68 dB PSNR gain over baseline 3DGS on Tanks&Temples and Mip-NeRF360.