An autoencoder plus regression network aligns 3D+t zebrafish embryo point clouds in time without manual annotation, with 3.83 minute average error on synthetic ground truth.
In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp
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Unsupervised Learning for Feature Extraction and Temporal Alignment of 3D+t Point Clouds of Zebrafish Embryos
An autoencoder plus regression network aligns 3D+t zebrafish embryo point clouds in time without manual annotation, with 3.83 minute average error on synthetic ground truth.