[CVPR'22] ICON: Implicit Clothed humans Obtained from Normals

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 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

Body measurements

Measure the SMPL body model

A Wiki on Body-Modelling Technology, maintained by Meshcapade GmbH.

AIST++ Dataset Webpage: https://google.github.io/aistplusplus_dataset

"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.

A real time virtual try-on application using SMPL models and OpenCV

Code used in the GRADE framework to convert SMPL animation data to the USD file format to be used in the IsaacSim/Omniverse simulators.

The Fast Way From Vertices to Parametric 3D Humans

➿A rerun plugin and tools for 3D animation

A way to visualize clothes on custom body measurements.

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.

Multi-modal Human Mesh Recovery (SMPL) using image and LiDAR data

A 100% compatiable SMPL,SMPL-H,SMPL-X model implemention in C++ with CUDA support. Same api with python smplx.