Human 3D model partiality representation via Mean Curvature Flow
-
Updated
Oct 17, 2022 - Python
Human 3D model partiality representation via Mean Curvature Flow
Enables users to create a profile saved only to local storage and get size recommendations across sites. This is the ultimate size recommendation plugin, saving time & money for online shoppers as it uses CV to predict body measurements and GPT 4 to provide size recommendations specific to a brand.
A 100% compatiable SMPL,SMPL-H,SMPL-X model implemention in C++ with CUDA support. Same api with python smplx.
A way to visualize clothes on custom body measurements.
"Linear Regression vs. Deep Learning". The source code for a simple but effective baseline method for human body measurement estimation using only height and weight information about the person.
Code used in the GRADE framework to convert SMPL animation data to the USD file format to be used in the IsaacSim/Omniverse simulators.
AIST++ Dataset Webpage: https://google.github.io/aistplusplus_dataset
A real time virtual try-on application using SMPL models and OpenCV
A Wiki on Body-Modelling Technology, maintained by Meshcapade GmbH.
Measure the SMPL body model
CVPR 2022 - Official code repository for the paper: Accurate 3D Body Shape Regression using Metric and Semantic Attributes.
Official implementation of CVPR2020 paper "Learning to Dress 3D People in Generative Clothing" https://arxiv.org/abs/1907.13615
API to support AIST++ Dataset: https://google.github.io/aistplusplus_dataset
[CVPR 2023] Official implementation of the paper "One-Stage 3D Whole-Body Mesh Recovery with Component Aware Transformer"
[CVPR'22] ICON: Implicit Clothed humans Obtained from Normals
Add a description, image, and links to the smpl-model topic page so that developers can more easily learn about it.
To associate your repository with the smpl-model topic, visit your repo's landing page and select "manage topics."