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This paper introduces TT4D, a novel pipeline and large-scale dataset for reconstructing table tennis gameplay in 4D from monocular videos. It features a unique lift-first approach that estimates 3D ball trajectories and spin before time segmentation, enabling robust reconstruction even with occlusions.