CAT-3DGS Pro: A New Benchmark for Efficient 3DGS Compression

• URL: http://arxiv.org/abs/2503.12862v1
• Date: Mon, 17 Mar 2025 06:45:10 GMT
• Title: CAT-3DGS Pro: A New Benchmark for Efficient 3DGS Compression
• Authors: Yu-Ting Zhan, He-bi Yang, Cheng-Yuan Ho, Jui-Chiu Chiang, Wen-Hsiao Peng,
• Abstract summary: 3D Gaussian Splatting (3DGS) has shown immense potential for novel view synthesis.<n> achieving rate-distortion-optimized compression of 3DGS representations for transmission and/or storage applications remains a challenge.<n>We propose CAT-3DGS Pro, an enhanced version of CAT-3DGS that improves both compression performance and computational efficiency.
• Score: 7.544406490280833
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: 3D Gaussian Splatting (3DGS) has shown immense potential for novel view synthesis. However, achieving rate-distortion-optimized compression of 3DGS representations for transmission and/or storage applications remains a challenge. CAT-3DGS introduces a context-adaptive triplane hyperprior for end-to-end optimized compression, delivering state-of-the-art coding performance. Despite this, it requires prolonged training and decoding time. To address these limitations, we propose CAT-3DGS Pro, an enhanced version of CAT-3DGS that improves both compression performance and computational efficiency. First, we introduce a PCA-guided vector-matrix hyperprior, which replaces the triplane-based hyperprior to reduce redundant parameters. To achieve a more balanced rate-distortion trade-off and faster encoding, we propose an alternate optimization strategy (A-RDO). Additionally, we refine the sampling rate optimization method in CAT-3DGS, leading to significant improvements in rate-distortion performance. These enhancements result in a 46.6% BD-rate reduction and 3x speedup in training time on BungeeNeRF, while achieving 5x acceleration in decoding speed for the Amsterdam scene compared to CAT-3DGS.

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