ClunoGS: Compact Language 3D Gaussian Splatting via Unified Optimization
Language 3D Gaussian Splatting enables open-vocabulary scene understanding by associating Gaussian primitives with language features.
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Key points
- These semantic attributes increase model storage, while most existing 3DGS compression methods are designed mainly to preserve RGB rendering quality.
- We propose ClunoGS, a compact framework for Language 3DGS that combines semantics-aware Gaussian sparsification and vector quantization in a unified constrained objective.
- We evaluate ClunoGS on open-vocabulary localization and segmentation using the LERF and ScanNet-10 benchmarks.
- Under aggressive compression, our unified, semantics-aware formulation substantially alleviates the degradation of semantic representations caused by sequential compression and semantics-agnostic Gaussian sparsification.
Sources (1)
- [1]ClunoGS: Compact Language 3D Gaussian Splatting via Unified OptimizationarXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 21, 04:43 PM
Language 3D Gaussian Splatting enables open-vocabulary scene understanding by associating Gaussian primitives with language features.
These semantic attributes increase model storage, while most existing 3DGS compression methods are designed mainly to preserve RGB rendering quality.
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