Differential rendering based motion capture blender project.

Overview

TraceArmature Summary

TraceArmature is currently a set of python scripts that allow for high fidelity motion capture through the use of AI pose estimation (using METRABS), fiducial markers, VR body trackers, and optional hand annotations. This information is applied to a rigged 3D scan of the subject and further refined using differentiable rendering and AKAZE features. Eventually, this project will be made into a blender plugin. The purpose of this project is to allow for UV mapping of an arbitrary target (human or non-human) with higher fidelity than is possible with AI pose estimation alone and with more accuracy and control than dense pose estimation. The depth and UV information gathered can be used to aid in style transfer techniques like Adobe's patch match algorithm or various neural style transfer methods. It is important to note that the aim of this project is accuracy, not speed. Running the highest quality UV reconstruction can take around 30 seconds per frame.

It is important to note that this project is still under HEAVY development, so formal instructions will be delayed until a stable, user-friendly build is ready.

Wireframe Motion Tracking Demo

Owner
William Rodriguez
Computer Engineering University Of Florida
William Rodriguez
Predict bus arrival time using VertexAI and Nvidia's Jetson Nano

bus_prediction predict bus arrival time using VertexAI and Nvidia's Jetson Nano imagenet the command for imagenet.py look like this python3 /path/to/i

10 Dec 22, 2022
Official and maintained implementation of the paper "OSS-Net: Memory Efficient High Resolution Semantic Segmentation of 3D Medical Data" [BMVC 2021].

OSS-Net: Memory Efficient High Resolution Semantic Segmentation of 3D Medical Data Christoph Reich, Tim Prangemeier, Özdemir Cetin & Heinz Koeppl | Pr

Christoph Reich 23 Sep 21, 2022
Official code for Next Check-ins Prediction via History and Friendship on Location-Based Social Networks (MDM 2018)

MUC Next Check-ins Prediction via History and Friendship on Location-Based Social Networks (MDM 2018) Performance Details for Accuracy: | Dataset

Yijun Su 3 Oct 09, 2022
Backend code to use MCPI's python API to make infinite worlds with custom generation

inf-mcpi Backend code to use MCPI's python API to make infinite worlds with custom generation Does not save player-placed blocks! Generation is still

5 Oct 04, 2022
Pytorch implementation for the EMNLP 2020 (Findings) paper: Connecting the Dots: A Knowledgeable Path Generator for Commonsense Question Answering

Path-Generator-QA This is a Pytorch implementation for the EMNLP 2020 (Findings) paper: Connecting the Dots: A Knowledgeable Path Generator for Common

Peifeng Wang 33 Dec 05, 2022
In this project we use both Resnet and Self-attention layer for cat, dog and flower classification.

cdf_att_classification classes = {0: 'cat', 1: 'dog', 2: 'flower'} In this project we use both Resnet and Self-attention layer for cdf-Classification.

3 Nov 23, 2022
Code release for NeX: Real-time View Synthesis with Neural Basis Expansion

NeX: Real-time View Synthesis with Neural Basis Expansion Project Page | Video | Paper | COLAB | Shiny Dataset We present NeX, a new approach to novel

538 Jan 09, 2023
Unofficial pytorch-lightning implement of Mip-NeRF

mipnerf_pl Unofficial pytorch-lightning implement of Mip-NeRF, Here are some results generated by this repository (pre-trained models are provided bel

Jianxin Huang 159 Dec 23, 2022
Official implementation of Deep Burst Super-Resolution

Deep-Burst-SR Official implementation of Deep Burst Super-Resolution Publication: Deep Burst Super-Resolution. Goutam Bhat, Martin Danelljan, Luc Van

Goutam Bhat 113 Dec 19, 2022
Scrutinizing XAI with linear ground-truth data

This repository contains all the experiments presented in the corresponding paper: "Scrutinizing XAI using linear ground-truth data with suppressor va

braindata lab 2 Oct 04, 2022
Unsupervised phone and word segmentation using dynamic programming on self-supervised VQ features.

Unsupervised Phone and Word Segmentation using Vector-Quantized Neural Networks Overview Unsupervised phone and word segmentation on speech data is pe

Herman Kamper 13 Dec 11, 2022
Playing around with FastAPI and streamlit to create a YoloV5 object detector

FastAPI-Streamlit-based-YoloV5-detector Playing around with FastAPI and streamlit to create a YoloV5 object detector It turns out that a User Interfac

2 Jan 20, 2022
U-Net for GBM

My Final Year Project(FYP) In National University of Singapore(NUS) You need Pytorch(stable 1.9.1) Both cuda version and cpu version are OK File Str

PinkR1ver 1 Oct 27, 2021
Understanding and Overcoming the Challenges of Efficient Transformer Quantization

Transformer Quantization This repository contains the implementation and experiments for the paper presented in Yelysei Bondarenko1, Markus Nagel1, Ti

83 Dec 30, 2022
This is the official source code for SLATE. We provide the code for the model, the training code, and a dataset loader for the 3D Shapes dataset. This code is implemented in Pytorch.

SLATE This is the official source code for SLATE. We provide the code for the model, the training code and a dataset loader for the 3D Shapes dataset.

Gautam Singh 66 Dec 26, 2022
Mmdet benchmark with python

mmdet_benchmark 本项目是为了研究 mmdet 推断性能瓶颈,并且对其进行优化。 配置与环境 机器配置 CPU:Intel(R) Core(TM) i9-10900K CPU @ 3.70GHz GPU:NVIDIA GeForce RTX 3080 10GB 内存:64G 硬盘:1T

杨培文 (Yang Peiwen) 24 May 21, 2022
Husein pet projects in here!

project-suka-suka Husein pet projects in here! List of projects mysejahtera-density. Generate resolution points using meshgrid and request each points

HUSEIN ZOLKEPLI 47 Dec 09, 2022
Scheme for training and applying a label propagation framework

Factorisation-based Image Labelling Overview This is a scheme for training and applying the factorisation-based image labelling (FIL) framework. Some

Wellcome Centre for Human Neuroimaging 2 Dec 17, 2021
Understanding the Generalization Benefit of Model Invariance from a Data Perspective

Understanding the Generalization Benefit of Model Invariance from a Data Perspective This is the code for our NeurIPS2021 paper "Understanding the Gen

1 Jan 15, 2022
This repository contains the source code and data for reproducing results of Deep Continuous Clustering paper

Deep Continuous Clustering Introduction This is a Pytorch implementation of the DCC algorithms presented in the following paper (paper): Sohil Atul Sh

Sohil Shah 197 Nov 29, 2022