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DeRF: Decomposed Radiance Fields

CVPR 2021 · 3D vision › NeRF and radiance fields · approach: Sparse-input NeRF regularization · 170 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Increase the number of Voronoi heads at the same render costDeRF · Real Forward-Facing scenesrendering qualityHelped
Use Voronoi decomposition rather than MLP-based decomposition (ablation)DeRF · roomrender time: 55.88s vs 32.89s; 76.51s vs 63.40s; 83.50s vs 127.32sMixed
Replace fixed grid cells with learned Voronoi cells (ablation)DeRF · roomPSNR: 28.07 -> 28.55Helped
Replace fixed grid cells with learned Voronoi cells (ablation)DeRF · roomSSIM: 0.88 -> 0.89Helped
Replace fixed grid cells with learned Voronoi cells (ablation)DeRF · roomLPIPS: 0.28 -> 0.25Helped
Increase network capacity instead of decomposing the sceneNeRF · ferninference timeHurt
Train the decomposition before training the per-cell network headsDeRF · trainingtraining stabilityHelped
Allow the uniformity loss to update the coarse density network (ablation)DeRF pre-training · trainingtraining stabilityHurt
Use a fixed grid instead of a learned decomposition (ablation)DeRF · roomrendering quality: 28.55 vs 28.07 PSNR; 0.89 vs 0.88 SSIM; 0.25 vs 0.28 LPIPSHurt
Increase DeRF decomposition headsDeRF · rendering qualityrendering qualityMixed
Use a regular grid decomposition (ablation)DeRF · real scenesaccuracyHurt

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