Splatwizard: A Benchmark Toolkit for 3D Gaussian Splatting Compression
- URL: http://arxiv.org/abs/2512.24742v1
- Date: Wed, 31 Dec 2025 09:26:04 GMT
- Title: Splatwizard: A Benchmark Toolkit for 3D Gaussian Splatting Compression
- Authors: Xiang Liu, Yimin Zhou, Jinxiang Wang, Yujun Huang, Shuzhao Xie, Shiyu Qin, Mingyao Hong, Jiawei Li, Yaowei Wang, Zhi Wang, Shu-Tao Xia, Bin Chen,
- Abstract summary: We introduce Splatwizard, a unified benchmark toolkit designed specifically for 3DGS compression models.<n>Splatwizard provides an easy-to-use framework to implement new 3DGS compression model and utilize state-of-the-art techniques.
- Score: 69.94586602640355
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: The recent advent of 3D Gaussian Splatting (3DGS) has marked a significant breakthrough in real-time novel view synthesis. However, the rapid proliferation of 3DGS-based algorithms has created a pressing need for standardized and comprehensive evaluation tools, especially for compression task. Existing benchmarks often lack the specific metrics necessary to holistically assess the unique characteristics of different methods, such as rendering speed, rate distortion trade-offs memory efficiency, and geometric accuracy. To address this gap, we introduce Splatwizard, a unified benchmark toolkit designed specifically for benchmarking 3DGS compression models. Splatwizard provides an easy-to-use framework to implement new 3DGS compression model and utilize state-of-the-art techniques proposed by previous work. Besides, an integrated pipeline that automates the calculation of key performance indicators, including image-based quality metrics, chamfer distance of reconstruct mesh, rendering frame rates, and computational resource consumption is included in the framework as well. Code is available at https://github.com/splatwizard/splatwizard
Related papers
- Quantile Rendering: Efficiently Embedding High-dimensional Feature on 3D Gaussian Splatting [52.18697134979677]
Recent advancements in computer vision have successfully extended Open-vocabulary segmentation (OVS) to the 3D domain by leveraging 3D Gaussian Splatting (3D-GS)<n>Existing methods employ codebooks or feature compression, causing information loss, thereby degrading segmentation quality.<n>We introduce Quantile Rendering (Q-Render), a novel rendering strategy for 3D Gaussians that efficiently handles high-dimensional features while maintaining high fidelity.<n>Our framework outperforms state-of-the-art methods, while enabling real-time rendering with an approximate 43.7x speedup on 512-D feature maps.
arXiv Detail & Related papers (2025-12-24T04:16:18Z) - TinySplat: Feedforward Approach for Generating Compact 3D Scene Representation [38.50388562890992]
TinySplat is a complete feedforward approach for generating compact 3D scene representations.<n>Built upon standard feedforward 3DGS methods, TinySplat integrates a training-free compression framework.<n>Our framework requires only 25% of the encoding time and 1% of the decoding time.
arXiv Detail & Related papers (2025-06-11T07:47:19Z) - Compressing 3D Gaussian Splatting by Noise-Substituted Vector Quantization [14.71160140310766]
3D Gaussian Splatting (3DGS) has demonstrated remarkable effectiveness in 3D reconstruction, achieving high-quality results with real-time radiance field rendering.<n>However, a key challenge is the substantial storage cost: reconstructing a single scene typically requires millions of Gaussian splats, each represented by 59 floating-point parameters, resulting in approximately 1 GB of memory.<n>We propose a compression method by building separate attribute codebooks and storing only discrete code indices. Specifically, we employ noise-substituted vector quantization technique to jointly train the codebooks and model features, ensuring consistency between descent gradient optimization and parameter discretization
arXiv Detail & Related papers (2025-04-03T22:19:34Z) - CAT-3DGS: A Context-Adaptive Triplane Approach to Rate-Distortion-Optimized 3DGS Compression [10.869104603083676]
3D Gaussian Splatting (3DGS) has recently emerged as a promising 3D representation.<n>The needs to compress and transmit the 3DGS representation to the remote side are overlooked.<n>This new application calls for rate-distortion-optimized 3DGS compression.
arXiv Detail & Related papers (2025-03-01T05:42:52Z) - Fast Feedforward 3D Gaussian Splatting Compression [55.149325473447384]
3D Gaussian Splatting (FCGS) is an optimization-free model that can compress 3DGS representations rapidly in a single feed-forward pass.<n>FCGS achieves a compression ratio of over 20X while maintaining fidelity, surpassing most per-scene SOTA optimization-based methods.
arXiv Detail & Related papers (2024-10-10T15:13:08Z) - 3DGS.zip: A survey on 3D Gaussian Splatting Compression Methods [10.122120872952296]
3D Gaussian Splatting (3DGS) has emerged as a cutting-edge technique for real-time radiance field rendering.<n>Despite its advantages in rendering speed and image fidelity, 3DGS is limited by its significant storage and memory demands.<n>This survey provides a detailed examination of compression and compaction techniques developed to make 3DGS more efficient.
arXiv Detail & Related papers (2024-06-17T11:43:38Z) - LP-3DGS: Learning to Prune 3D Gaussian Splatting [71.97762528812187]
We propose learning-to-prune 3DGS, where a trainable binary mask is applied to the importance score that can find optimal pruning ratio automatically.
Experiments have shown that LP-3DGS consistently produces a good balance that is both efficient and high quality.
arXiv Detail & Related papers (2024-05-29T05:58:34Z) - SAGS: Structure-Aware 3D Gaussian Splatting [53.6730827668389]
We propose a structure-aware Gaussian Splatting method (SAGS) that implicitly encodes the geometry of the scene.
SAGS reflects to state-of-the-art rendering performance and reduced storage requirements on benchmark novel-view synthesis datasets.
arXiv Detail & Related papers (2024-04-29T23:26:30Z) - CompGS: Efficient 3D Scene Representation via Compressed Gaussian Splatting [68.94594215660473]
We propose an efficient 3D scene representation, named Compressed Gaussian Splatting (CompGS)
We exploit a small set of anchor primitives for prediction, allowing the majority of primitives to be encapsulated into highly compact residual forms.
Experimental results show that the proposed CompGS significantly outperforms existing methods, achieving superior compactness in 3D scene representation without compromising model accuracy and rendering quality.
arXiv Detail & Related papers (2024-04-15T04:50:39Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.