SGIA: We achieve fast reconstruction of clothed human avatars with PBR properties from a monocular video. SGIA takes a monocular video and initial human pose and shape as input to estimate dynamic clothed humans' PBR properties, including geometry and materials. Leveraging a PBR-aware 2DGS representation, our method enables fast training and rendering processes. By utilizing the estimated PBR properties, we can not only deform the avatars into different poses but also render them with realistic lighting conditions, allowing for versatile and visually appealing outputs.
Main Experiment Comparison
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Novel Pose Animation at different View under different illumination
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