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Compact Neural Appearance Models for Efficient Gaussian Splatting

Paper recorded by Signals 4 on 2026-09-04 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-04 on arXiv · recorded by Signals 4 on 2026-09-07

Category: cs.CV · 计算机视觉 · first seen 2026-09-07

Abstract

Explicit primitive-based radiance fields such as 3D Gaussian Splatting typically model view-dependent appearance using low-order spherical harmonics (SH). Although efficient to evaluate, SH coefficients dominate per-primitive storage and memory traffic, while their band-limited basis restricts angular detail. We present a thorough, end-to-end comparison of SH and recent spherical appearance models

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#137 most recent of 237 cs.CV papers we have recorded · ↑ newer: Learning Spatial-Spectral Refinement and Calibrating Complementary Obs · ↓ older: Few-Shot Video Recognition via Hierarchical Metric Learning
Cite this page: Compact Neural Appearance Models for Efficient Gaussian Splatting: the #137 most recent of 237 cs.CV papers we have recorded (as of 2026-09-04). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/compact-neural-appearance-models-for-efficient-gaussian-splatting.html
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