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.
Fully automated landmarking and facial segmentation on 3D photographs. B Berends, F Bielevelt, R Schreurs, et al.
A deep learning-based approach for automated landmark extraction from 3dMD facial photographs was developed and its precision was evaluated. The results showed high precision and consistency in landmark annotation, comparable to manual and semi-automatic annotation methods.
A quantitative method for the assessment of facial attractiveness based on transfer learning with fine-grained image classification. LJ Lo, CT Yang, WC Chiang, HH Lin.
3dMD facial images and deep transfer learning have been firstly combined for evaluating the facial attractiveness in patients undergoing Orthognathic surgery.
Accurate estimation of biological age and its application in disease prediction using a multimodal image Transformer system. J Wang, Y Gao, F Wang, S Zeng, J Li, H Miao, T Wang, J Zeng, D Baptista-Hon, O Monteiro, T Guan, L Cheng, Y Lu, Z Luo, M Li, J Zhu, S Nie, K Zhang, Y Zhou.
Applying standard acquisition protocols, 3D neutral expression facial images were captured using 3dMDface systems of participants during their annual visits from 2018 to 2022.
The Florence multi-resolution 3D facial expression dataset. C Ferrari, S Berretti, P Pala, A Del Bimbo.
University of Florence builds Florence 3DMRE (2023), a cross-resolution facial dataset, with 3dMD’s real-world high-resolution face scans.
Handy: Towards a high fidelity 3D hand shape and appearance model. R Potamias, S Ploumpis, S Moschoglou, V Triantafyllou and S Zafeiriou.
How 3dMD’s 4D real-world hand data enabled Handy, Imperial College London’s 2023 model of hand shape and appearance.
Multilevel Functional Principal Components Analysis Presents a Viable Method of Modelling Dynamical Shape Changes. DJJ Farnell, P Claes.
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The Florence 4D Facial Expression Dataset. F Principi, S Berretti, C Ferrari, N Otberdout, M Daoudi, A Del Bimbo
University of Florence builds Florence 4D (2023), a dynamic facial expression dataset, with 3dMD’s real-world 3D face scans.
SUPR: A Sparse Unified Part-Based Human Representation. AAA Osman, T Bolkart, D Tzionas, MJ Black.
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.
MimicME: A Large Scale Diverse 4D Database for Facial Expression Analysis. A Papaioannou et al.
Imperial College London captures real-world MimicMe, a 4,700-subject 4D facial expression database, with 3dMD, presented at ECCV 2022.