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arXivOctober 27, 2026

RacerGS: Residual-Autoregressive Context for 3D Gaussian Splatting Compression

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본 논문은 3D Gaussian Splatting(3DGS)의 큰 파라미터 크기 문제를 해결하기 위한 압축 프레임워크 RacerGS를 제안합니다. 이 방법은 해시 투영 모델과 자기회귀 GRU 컨텍스트 모델을 결합하여 장면 재구성을 수행합니다. 그 결과, 기존 3DGS 대비 150배 이상의 높은 압축률을 달성하면서도 뛰어난 렌더링 품질을 유지함을 입증했습니다.

3d gaussian splatting
compression
autoregressive
novel view rendering
racergs

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RacerGS: Residual-Autoregressive Context for 3D Gaussian Splatting Compression

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