[CVPR'22] ICON: Implicit Clothed humans Obtained from Normals
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Updated
Nov 23, 2023 - Python
[CVPR'22] ICON: Implicit Clothed humans Obtained from Normals
[CVPR 2023] Official implementation of the paper "One-Stage 3D Whole-Body Mesh Recovery with Component Aware Transformer"
API to support AIST++ Dataset: https://google.github.io/aistplusplus_dataset
Official implementation of CVPR2020 paper "Learning to Dress 3D People in Generative Clothing" https://arxiv.org/abs/1907.13615
CVPR 2022 - Official code repository for the paper: Accurate 3D Body Shape Regression using Metric and Semantic Attributes.
Measure the SMPL body model
A Wiki on Body-Modelling Technology, maintained by Meshcapade GmbH.
A real time virtual try-on application using SMPL models and OpenCV
AIST++ Dataset Webpage: https://google.github.io/aistplusplus_dataset
Code used in the GRADE framework to convert SMPL animation data to the USD file format to be used in the IsaacSim/Omniverse simulators.
"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 way to visualize clothes on custom body measurements.
A 100% compatiable SMPL,SMPL-H,SMPL-X model implemention in C++ with CUDA support. Same api with python smplx.
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 rerun plugin and tools for 3D animation
Human 3D model partiality representation via Mean Curvature Flow
Multi-modal Human Mesh Recovery (SMPL) using image and LiDAR data
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