Synthesizing Facial Photometries and Corresponding Geometries Using Generative Adversarial Networks. G Shamai, R Slossberg, R Kimmel.

3dMD Customer Research, Normative Study, 3dMDface, 3dMDhead, Computer Science, Temporal-3D Systems (4D), 4D 3dMDface/head System, Computer Vision

Date: October 2019. Source: ACM Transactions on Multimedia Computing, Communications, and Applications, Article No.: 87 https://doi.org/10.1145/3337067. Abstract: Artificial data synthesis is currently a well-studied topic with useful applications in data science, computer vision, graphics, and many other fields. Generating realistic data is especially challenging, since human perception is highly sensitive to non-realistic appearance. In recent…

Synthesizing Coupled 3D Face Modalities by Trunk-Branch Generative Adversarial Networks. B Gecer, A Lattas, S Ploumpis, et al.

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

Date: September 2019. Source: Cornell University Library – arXiv.org, Computer Vision and Pattern Recognition. Abstract: Generating realistic 3D faces is of high importance for computer graphics and computer vision applications. Generally, research on 3D face generation revolves around linear statistical models of the facial surface. Nevertheless, these models cannot represent faithfully either the facial texture…

The Influence of Visual Perspective on Body Size Estimation in Immersive Virtual Reality. A Thaler, S Pujades, JK Stefanucci, SH Creem-Regehr, J Tesch, MJ Black, and BJ Mohler

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

Date: September 2019. Source: ACM Symposium on Applied Perception 2019, University of Barcelona, Spain. Abstract: The creation of realistic self-avatars that users identify with is important for many virtual reality applications. However, current approaches for creating biometrically plausible avatars that represent a particular individual require expertise and are time-consuming. We investigated the visual perception of…

A machine learning framework for automated diagnosis and computer-assisted planning in plastic and reconstructive surgery. PGM Knoops, A Papaioannou, A Borghi, et al.

3dMD Customer Research, 3dMDface, Computer Science, 3dMDface System, Computer Vision

Date: September 2019. Source: Scientific Reports 9, 13597 (2019). Abstract: Current computational tools for planning and simulation in plastic and reconstructive surgery lack sufficient precision and are time-consuming, thus resulting in limited adoption. Although computer-assisted surgical planning systems help to improve clinical outcomes, shorten operation time and reduce cost, they are often too complex and…

Capture, Learning, and Synthesis of 3D Speaking Styles. D Cudeiro, T Bolkart, C Laidlaw, A Ranjan, MJ Black.

3dMD Customer Research, Normative Study, 3dMDface, 3dMDhead, Computer Science, 4D 3dMDface/head 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): 10093-10103. Abstract: Audio-driven 3D facial animation has been widely explored, but achieving realistic, human-like performance is still unsolved. This is due to the lack of available 3D datasets, models, and standard evaluation metrics. To address…

Learning to Regress 3D Face Shape and Expression from an Image without 3D Supervision. S Sanyal, T Bolkart, H Feng, MJ Black.

3dMD Customer Research, Normative Study, 3dMDface, 3dMDhead, Computer Science, Temporal-3D Systems (4D), 4D 3dMDface/head 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): 7755-7764. Abstract: The estimation of 3D face shape from a single image must be robust to variations in lighting, head pose, expression, facial hair, makeup, and occlusions. Robustness requires a large training set of in-the-wild…

Dense 3D Face Decoding Over 2500FPS: Joint Texture and Shape Convolutional Mesh Decoders. Y Zhou, Ji Deng, I Kotsia, S Zafeiriou.

3dMD Customer Research, Normative Study, Computer Science, Computer Vision

Date: June 2019. Source: 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, CA, USA. Abstract: 3D Morphable Models (3DMMs) are statistical models that represent facial texture and shape variations using a set of linear bases and more particular Principal Component Analysis (PCA). 3DMMs were used as statistical priors for reconstructing 3D…

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…