We introduce PoreTrack3D, the first benchmark for dynamic 3D Gaussian splatting in pore-scale, non-rigid 3D facial trajectory tracking. It contains over 440,000 facial trajectories in total, among which more than 52,000 are longer than 10 frames, including 68 manually reviewed trajectories that span the entire 150 frames. To the best of our knowledge, PoreTrack3D is the first benchmark dataset to capture both traditional facial landmarks and pore-scale keypoints trajectory, advancing the study of fine-grained facial expressions through the analysis of subtle skin-surface motion. We systematically evaluate state-of-the-art dynamic 3D Gaussian splatting methods on PoreTrack3D, establishing the first performance baseline in this domain. Overall, the pipeline developed for this benchmark dataset's creation establishes a new framework for high-fidelity facial motion capture and dynamic 3D reconstruction. Our dataset are publicly available at: https://github.com/JHXion9/PoreTrack3D

翻译：本文提出了PoreTrack3D，这是首个面向毛孔尺度非刚性三维面部轨迹跟踪的动态3D高斯泼溅基准数据集。该数据集共包含超过44万条面部运动轨迹，其中超过5.2万条轨迹长度大于10帧，并包含68条经人工审核、贯穿全部150帧的完整轨迹。据我们所知，PoreTrack3D是首个同时捕获传统面部关键点与毛孔尺度特征点轨迹的基准数据集，通过分析皮肤表面的细微运动，推动了细粒度面部表情研究的发展。我们在PoreTrack3D上系统评估了当前最先进的动态3D高斯泼溅方法，首次建立了该领域的性能基线。总体而言，构建该基准数据集的技术流程为高保真面部运动捕捉与动态三维重建建立了全新框架。本数据集已公开于：https://github.com/JHXion9/PoreTrack3D