Structure-Guided 2D Gaussian Splatting for Image Compression
Research Paper#Image Compression, 2D Gaussian Splatting, Computer Vision🔬 Research|Analyzed: Jan 3, 2026 18:21•
Published: Dec 30, 2025 06:35
•1 min read
•ArXivAnalysis
This paper addresses the limitations of 2D Gaussian Splatting (2DGS) for image compression, particularly at low bitrates. It introduces a structure-guided allocation principle that improves rate-distortion (RD) efficiency by coupling image structure with representation capacity and quantization precision. The proposed methods include structure-guided initialization, adaptive bitwidth quantization, and geometry-consistent regularization, all aimed at enhancing the performance of 2DGS while maintaining fast decoding speeds.
Key Takeaways
- •Proposes a structure-guided allocation principle for 2D Gaussian Splatting to improve image compression.
- •Introduces structure-guided initialization, adaptive bitwidth quantization, and geometry-consistent regularization.
- •Achieves significant improvements in rate-distortion performance while maintaining fast decoding speeds (over 1000 FPS).
- •Demonstrates substantial BD-rate reduction compared to baseline methods.
Reference / Citation
View Original"The approach substantially improves both the representational power and the RD performance of 2DGS while maintaining over 1000 FPS decoding. Compared with the baseline GSImage, we reduce BD-rate by 43.44% on Kodak and 29.91% on DIV2K."