VideoMDM learns coherent 3D motion manifolds from 2D supervision alone by using a pretrained lifter as noisy teacher, depth-weighted 2D reprojection loss, and adapted regularizers, nearly matching fully 3D-supervised performance on HumanML3D.
arXiv preprint arXiv:2407.04237 (2024)
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A literature survey that compiles ten years of 3D scene completion research, builds a taxonomy of representation paradigms, and outlines a future research agenda.
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VideoMDM: Towards 3D Human Motion Generation From 2D Supervision
VideoMDM learns coherent 3D motion manifolds from 2D supervision alone by using a pretrained lifter as noisy teacher, depth-weighted 2D reprojection loss, and adapted regularizers, nearly matching fully 3D-supervised performance on HumanML3D.
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Deep Learning Approaches for 3D Medical Scene Completion: From Geometric Modeling to Generative Paradigms
A literature survey that compiles ten years of 3D scene completion research, builds a taxonomy of representation paradigms, and outlines a future research agenda.