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About this paper
Muhammad Salman Ali, Chaoning Zhang, Marco Cagnazzo, Giuseppe Valenzise, Enzo Tartaglione, Sung-Ho Bae
A comprehensive survey systematically reviews and categorizes compression techniques for 3D Gaussian Splatting (3DGS), proposing a novel taxonomy of unstructured and structured methods to address the technology's substantial memory footprint. The analysis highlights that unstructured methods achieve significant FPS improvements (4x-7x faster) with good compression (up to 55x), while structured methods provide superior compression ratios (up to 188x) with comparable rendering speeds, charting a path for optimizing 3DGS for resource-constrained applications.
Key insights
- Unstructured compression methods for 3D Gaussian Splatting (3DGS) provide substantial rendering speed improvements (4x-7x faster FPS) with good compression ratios (typically 8x-55x), making them suitable for real-time applications.
- Structured compression methods achieve significantly higher compression ratios (70x-188x) by leveraging spatial organization, albeit often maintaining rendering speeds comparable to or slightly lower than the 3DGS baseline due to computational overhead.
- The survey identifies key challenges, including scalability for very large scenes, the need for hardware-efficient scalar quantization, and underexplored impacts of different loss functions on compression performance, suggesting inspirations from NeRF and point cloud compression.
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