Expressive Body Capture: 3D Hands, Face, and Body from a Single Image. G Pavlakos, V Choutas, N Ghorbani, T Bolkart, AA Osman, D Tzionas, MJ Black.

3dMD Customer Research, 3dMDhand, Computer Science, Temporal-3D Systems (4D), 4D 3dMDhand System, Computer Vision

Date: June 2019. Source: 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, CA, USA. Proceedings Page(s): 10967-10977. Abstract: To facilitate the analysis of human actions, interactions and emotions, we compute a 3D model of human body pose, hand pose, and facial expression from a single monocular image. To achieve this, we…

3DFaceGAN: Adversarial Nets for 3D Face Representation, Generation, and Translation. S Moschoglou, S Ploumpis, MA Nicolaou et al.

3dMD Customer Research, Normative Study, 3dMDface, 3dMDhead, Computer Science, 4D 3dMDface/head System, Computer Vision

Date: May 2019. Source: International Journal of Computer Vision (2020). https://doi.org/10.1007/s11263-020-01329-8. Abstract: Over the past few years, Generative Adversarial Networks (GANs) have garnered increased interest among researchers in Computer Vision, with applications including, but not limited to, image generation, translation, imputation, and super-resolution. Nevertheless, no GAN-based method has been proposed in the literature that can…

MeshMonk: Open-source large-scale intensive 3D phenotyping. JD White, A Ortega-Castrillón, H Matthews et al.

3dMD Customer Research, Computer Science | Computer Vision, Medical, 3dMDface, Computer Science, Morphometrics, 3dMDface System, Computer Vision

Date: April 2019. Source: Scientific Reports 9, 6085. https://doi.org/10.1038/s41598-019-42533-y. Abstract: Dense surface registration, commonly used in computer science, could aid the biological sciences in accurate and comprehensive quantification of biological phenotypes. However, few toolboxes exist that are openly available, non-expert friendly, and validated in a way relevant to biologists. Here, we report a customizable toolbox…

AMASS: Archive of Motion Capture as Surface Shapes. N Mahmood , N Ghorbani, NF Troje, G Pons-Moll, MJ Black.

3dMD Customer Research, Size & Fit | Wearable Tech | Apparel | Product Design, Computer Science, Size & Fit, Temporal-3D Systems (4D), Computer Vision

Date: April 2019. Source: Cornell University Library – arXiv.org, Computer Vision and Pattern Recognition. Abstract: Large datasets are the cornerstone of recent advances in computer vision using deep learning. In contrast, existing human motion capture (mocap) datasets are small and the motions limited, hampering progress on learning models of human motion. While there are many…

MeshGAN: Non-linear 3D Morphable Models of Faces. S Cheng, M Bronstein, Y Zhou, I Kotsia, M Pantic, S Zafeiriou.

3dMD Customer Research, Computer Science | Computer Vision, Psychology, Computer Science, Morphometrics, Temporal-3D Systems (4D)

Date: April 2019. Source: Cornell University Library – arXiv.org, Computer Vision and Pattern Recognition. Abstract: Generative Adversarial Networks (GANs) are currently the method of choice for generating visual data. Certain GAN architectures and training methods have demonstrated exceptional performance in generating realistic synthetic images (in particular, of human faces). However, for 3D object, GANs still…

Intelligent Harvesting of High-Precision 4D Data of Human Subjects in a Personalized Digital Economy. Chris Lane.

3dMD Customer Research, Human Factors | Anthropometric, Size & Fit | Wearable Tech | Apparel | Product Design, Sports Science, 3dMD News, Anthropometric, Apparel, Computer Science, Size & Fit, Temporal-3D Systems (4D), News

Date: October 2018. Source: 9th 3DBODY.TECH Conference and Expo. October 16-17, 2018. Lugano, Switzerland, USA. Presenter: Chris LANE, 3dMD Ltd. Session: Technical Session 10: Full Body Scanning & Processing

Potential of 3D Surface Imaging for Quantitative Analysis of Fat Grafting. MK Markey, F Merchant, GP Reece et al.

3dMD Customer Research, Medical, Computer Science, Plastics, 3dMDtorso System, 3dMDthorax

Date: October 2018. Source: 9th 3DBODY.TECH Conference and Expo. October 16-17, 2018. Lugano, Switzerland, USA. Presenter: Mia K Markey Session: Technical Session 3: 3D Face & Body Scanning in Medicine Abstract: Autologous fat grafting is increasingly employed to address volume asymmetry and contour irregularity following breast reconstruction for breast cancer. However, there are no well-established…

Effect of surrogate design on the measured stiffness of snowboarding wrist protectors. C Adams, D James, T Senior, T Allen, N Hamilton.

3dMD Customer Research, Size & Fit | Wearable Tech | Apparel | Product Design, Sports Science, 3D Printing, Computer Science, Size & Fit, 3dMDthorax System, 3dMDthorax

Date: September 2018. Source: Sports Engineering, Volume 21, Issue 3, pp 217–225. Abstract: In snowboarding, the wrist is the most common injury site, as snowboarders often put their arms out to cushion a fall. This can result in a compressive load through the carpals coupled with wrist hyperextension, leading to ligament sprains or carpal and…

DeepWrinkles: Accurate and Realistic Clothing Modeling. Zorah Lähner, Daniel Cremers, Tony Tung.

3dMD Customer Research, Computer Science | Computer Vision, Size & Fit | Wearable Tech | Apparel | Product Design, Computer Science, Size & Fit, Temporal-3D Systems (4D)

Date: September 2018. Source: 15th European Conference on Computer Vision (ECCV), Munich, Germany. Abstract: We present a novel method to generate accurate and realistic clothing deformation from real data capture. Previous methods for realistic cloth modeling mainly rely on intensive computation of physics-based simulation (with numerous heuristic parameters), while models reconstructed from visual observations typically…

Generating 3D Faces using Convolutional Mesh Autoencoders. A Ranjan, T Bolkart, S Sanyal, MJ Black.

3dMD Customer Research, Computer Science, Temporal-3D Systems (4D)

Date: September 2018. Source: 15th European Conference on Computer Vision (ECCV), Munich, Germany, (pp 704-720). Abstract: Learned 3D representations of human faces are useful for computer vision problems such as 3D face tracking and reconstruction from images, as well as graphics applications such as character generation and animation. Traditional models learn a latent representation of…