CAPE dataset is released! Please register first to access the downloads. 19th century date for the cape is most probable (Hugo Zopi, pers. 20 sequences of high quality raw scans for several subjects are available (upon request) now! Please first register on our website, and send us the signed consent form (available in the "Downloads" section once logged in) for raw scan data. Spectrometry Laboratory in Seattle, Washington. SCANimate: creating an avatar with pose-dependent clothing deformation from raw scans without template surface registration!.SCALE: Modeling pose-dependent shapes of clothed humans explicitly with hundreds of articulated surface elements: the clothing deforms naturally even in the presence of topological change!.Check out our new papers to appear in CVPR 2021, both use CAPE data! POP: a point-based, unified model for multiple subjects and outfits that can turn a single, static 3D scan into an animatable avatar with natural pose-dependent clothing deformations.Check out our new work at ICCV 2021, trained with CAPE data: Please check out the bottom of the download page for more information. We now provide packed CAPE data that are compatible with POP and SCALE. The model, code and data are available for research purposes at this website. To our knowledge, this is the first generative model that directly dresses 3D human body meshes and generalizes to different poses. added No Sew Kid's Capes to Projects to do 13 Sep 10:59 carmel.smith. Our model, named CAPE, represents global shape and fine local structure, effectively extending the SMPL body model to clothing. sweetstuffbymisty favorited No Sew Kid's Capes 12 Jul 22:24 Swellesely favorited No Sew Kid's Capes 23 Oct 00:39 Deanna G. To preserve wrinkle detail, our Mesh-VAE-GAN extends patchwise discriminators to 3D meshes. Our model is conditioned on both pose and clothing type, giving the ability to draw samples of clothing to dress different body shapes in a variety of styles and poses. Specifically, we train a conditional Mesh-VAE-GAN to learn the clothing deformation from the SMPL body model, making clothing an additional term on SMPL. To address this, we learn a generative 3D mesh model of clothed people from 3D scans with varying pose and clothing. Additionally, current models lack the expressive power needed to represent the complex non-linear geometry of pose-dependent clothing shape. Existing models, however, are learned from minimally-clothed 3D scans and thus do not generalize to the complexity of dressed people in common images and videos. Three-dimensional human body models are widely used in the analysis of human pose and motion.
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