Design2Cloth: 3D Cloth Generation from 2D Masks. J Zheng, RA Potamias, S Zafeiriou.
Imperial College London builds Design2Cloth (2024), a 3D garment generation model, with 3dMD’s real-world 2,010-subject dataset.
Training AI, Wearing Tech,
and Imaging Health.

Imperial College London builds Design2Cloth (2024), a 3D garment generation model, with 3dMD’s real-world 2,010-subject dataset.
To develop sports bras that effectively limiting breast movement while minimize stress on the breast tissues, it is crucial to gain a comprehensive understanding of the breast movement and deformation patterns.
Applying standard acquisition protocols, 3D neutral expression facial images were captured using 3dMDface systems of participants during their annual visits from 2018 to 2022.
Three-dimensional facial images of 2454 participants in the 3D Facial Norms (3DFN) project were obtained using the 3dMDface system.
University of Florence builds Florence 3DMRE (2023), a cross-resolution facial dataset, with 3dMD’s real-world high-resolution face scans.
At the age of nine and thirteen, three-dimensional (3D) facial images were taken of the children using a 3dMDface System (3dMD LLC, USA) photogrammetric device by trained photographers.
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University of Florence builds Florence 4D (2023), a dynamic facial expression dataset, with 3dMD’s real-world 3D face scans.
University of York and MBZUAI researchers use 3dMD’s real-world Headspace dataset to benchmark a new, faster method for registering 3D head scans to a shape template.
MPI-IS trains SUPR (2022), a full-body, hand, head, and foot model, with 3dMD’s real-world 4D scan data, presented at ECCV 2022.