标题： 3DGS-VBench：3DGS压缩的全面视频质量评估基准 显示英文标题

标题： 3DGS-VBench: A Comprehensive Video Quality Evaluation Benchmark for 3DGS Compression

摘要： 3D高斯点云（3DGS）能够在实时新视角合成中实现高视觉保真度，但其较大的存储需求阻碍了实际部署，促使最先进的（SOTA）3DGS方法引入压缩模块。 然而，这些3DGS生成式压缩技术引入了独特的失真，缺乏系统性的质量评估研究。 为此，我们建立了3DGS-VBench，一个大规模的视频质量评估（VQA）数据集和基准，包含660个压缩的3DGS模型以及从11个场景中通过6种SOTA 3DGS压缩算法生成的视频序列，并系统地设计了参数级别。 在50名参与者的注释下，我们获得了去除异常值后的MOS分数并验证了数据集的可靠性。 我们在存储效率和视觉质量方面对6种3DGS压缩算法进行了基准测试，并在多种范式下评估了15种质量评估指标。 我们的工作实现了针对3DGS的专用VQA模型训练，为压缩和质量评估研究提供了催化剂。 数据集可在https://github.com/YukeXing/3DGS-VBench获取。 显示英文摘要

摘要： 3D Gaussian Splatting (3DGS) enables real-time novel view synthesis with high visual fidelity, but its substantial storage requirements hinder practical deployment, prompting state-of-the-art (SOTA) 3DGS methods to incorporate compression modules. However, these 3DGS generative compression techniques introduce unique distortions lacking systematic quality assessment research. To this end, we establish 3DGS-VBench, a large-scale Video Quality Assessment (VQA) Dataset and Benchmark with 660 compressed 3DGS models and video sequences generated from 11 scenes across 6 SOTA 3DGS compression algorithms with systematically designed parameter levels. With annotations from 50 participants, we obtained MOS scores with outlier removal and validated dataset reliability. We benchmark 6 3DGS compression algorithms on storage efficiency and visual quality, and evaluate 15 quality assessment metrics across multiple paradigms. Our work enables specialized VQA model training for 3DGS, serving as a catalyst for compression and quality assessment research. The dataset is available at https://github.com/YukeXing/3DGS-VBench.