3D Gaussian Splatting
Dataset for PerfCam: Digital Twinning for Production Lines Using 3D Gaussian Splatting and Vision Models
KTH Royal Institute of Technology, SCI; AstraZeneca, Sweden Operations
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e used a mixed dataset\cite{ye2023geneface}in our experiments, where part of the data was referenced from the publicly available dataset provided by GaussianTalking\cite{li2025talkinggaussian}, and additional data was collected by ourselves. Specifically, we selected four high-definition talking video clips from the publicly available dataset, including two male portraits, "Macron" and "Obama" and one female portrait, "May". These video clips are centered on the subject, with an average length of 6500 frames and a frame rate of 25 FPS.
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3D Gaussian Splatting performs 3D reconstruction by densifying sparse point clouds into Gaussian ellipsoids of the order of 100,000, and the reconstruction results show excellent visual effects. However, the point cloud data derived from 3D Gaussian Splatting is not fully utilized in the reconstruction process. To this end, this paper proposes to optimize the point cloud data derived from 3D Gaussian Splatting to improve the rendering quality of 3D Gaussian Splatting. First, the sparse point cloud is input into 3D Gaussian Splatting for reconstruction.
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