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Deformable Radial Kernel Splatting

CVPR 2025 · 3D vision › Gaussian splatting · approach: Regularization and primitive design for 3DGS · 10 citations (OpenAlex)

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Proposes Deformable Radial Kernel (DRK), a generalized planar splatting primitive with learnable radial bases, L1/L2 blended distance, and edge sharpening, that represents complex shapes with far fewer primitives than Gaussian splatting.

Problem

Gaussian splatting primitives are radially symmetric and smooth, so representing sharp edges and diverse shapes requires thousands of Gaussians, causing inefficiency in memory and computation.

Approach

Replace the Gaussian kernel with a planar deformable radial kernel defined by learnable radial basis lengths and polar angles, blending L1 and L2 norms with a learnable weight, and applying a piecewise linear sharpening function; includes ray-primitive intersection depth sorting, polygon-based tile culling, and cache sorting.

Key results

Measured effects reported in the paper

What was changedWhereMeasuredEffect
replace Gaussian-based splatting with DRK3D scene rendering · DiverseScene averagePSNR: 35.68 -> 37.58Helped
replace Gaussian-based splatting with DRK3D scene rendering · DiverseScene averageprimitive count: 373K -> 260KMixed
use the sparser S1 density setting (ablation)DRK · DiverseScene averagePSNR: 37.58 -> 36.62Hurt
use the sparser S2 density setting (ablation)DRK · DiverseScene averagePSNR: 37.58 -> 35.03Hurt
use the sparser S1 density setting (ablation)DRK · DiverseSceneprimitive count: 260K -> 109KHelped
use the sparser S2 density setting (ablation)DRK · DiverseSceneprimitive count: 260K -> 42 KHelped
replace Gaussian-based splatting with DRK3D scene rendering · Mip-NeRF360LPIPS: .2688 -> .2364Helped
replace Gaussian-based splatting with DRK3D scene rendering · Mip-NeRF360PSNR: 26.94 -> 26.76Hurt
use the sparser S2 density setting (ablation)DRK · Mip-NeRF360PSNR: 26.76 -> 26.20Hurt
use the sparser S1 density setting (ablation)DRK · Mip-NeRF360SSIM: .7871 -> .7722Hurt

Surprising findings

Limitations

Experimental setup

Datasets: DiverseScenes Mip-NeRF360

Benchmarks: DiverseScenes Mip-NeRF360

Metrics: PSNR SSIM LPIPS M-PSNR primitive count model size FPS

Baselines: 3D-GS 2D-GS 3D-HGS GES 3D-GS (L)

Builds on: 3D Gaussian Splatting 2D Gaussian Splatting EWA splatting 3D-HGS GES

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