MeshGAN: Non-linear 3D Morphable Models of Faces. S Cheng, M Bronstein, Y Zhou, I Kotsia, M Pantic, S Zafeiriou.
Imperial College London trains MeshGAN (2019), a 3D face GAN, with 3dMD’s real-world 12,000-identity dataset.
Training AI, Wearing Tech,
and Imaging Health.

Imperial College London trains MeshGAN (2019), a 3D face GAN, with 3dMD’s real-world 12,000-identity dataset.
Imperial College London trains UV-GAN (2018) to complete facial textures, using 3dMD’s real captured 3D scans as its core dataset.
University of York and Alder Hey use 3dMD’s real-world Headspace dataset to train SA-CPD, a symmetry-aware shape morphing method for 3D face and head models.
University of York and Alder Hey use 3dMD’s real-world Headspace dataset to build the Liverpool-York Head Model (LYHM), the first public 3D morphable model of the full human head.
MPI-IS trains ClothCap (2017), a method for capturing and retargeting clothing in motion, with 3dMD’s 4D real-world body data.
Study at MRC Unit The Gambia (MRCG) which aims to assess whether babies conceived in the dry season have greater variation (asymmetry) than those conceived in the rains.
Imperial College London and Great Ormond Street build LSFM (2017), the largest 3D morphable model, with 3dMD’s real-world 12,000-scan dataset.
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Alder Hey Children’s Hospital uses 3dMD’s real-world Headspace dataset, 1,523 subjects, to build a morphable head profile model for scaphocephaly surgical outcomes.
University of York and Alder Hey Children’s Hospital use 3dMD’s real-world Headspace dataset to build the first automatic 3D statistical model of craniofacial form.