my graduation project is about live human face augmentation by projection mapping by using CNN

Overview

Live-human-face-expression-augmentation-by-projection

my graduation project is about live human face augmentation by projection mapping by using CNN our system is composed of three essential stages. The first stage is about using a modified function that uses Blendshape class in unity to take the in- put we got from the CNN model of the blendshapes values in C#. After that we create the dataset by gathering a collection of images and process it. We process the images by making our 3d model mimic the human facial expression in the image. the first phase of dataset processing, is making the 3d model expression natural, the second phase is trying the 74 blendshapes by changing the number of the blendshape from range 0 to 100 to get the best expression of 3d model that match the image, the third phase is saving these blendshapes values into a comma-separated values (CSV) file The second stage is to prepare the dataset for Convolutional Neural Network (CNN) model by resizing it and change the RGB color to the gray-scale image. First, we resize the image to 400×400 by using Keras APIs.Second, we change the RGB color to gray-scale color. The third stage is implementing the Convolutional Neural Network (CNN) model to take an input image and output its blendshapes values . Finally, we take the output and put it in the 3d model in unity

Screen Shot 2021-10-23 at 5 57 39 PM

the full project description in Live human face expression augmentation by projection1.pdf

ps: here are the bset weights i get it from cnn https://drive.google.com/file/d/1p0qo35m9r0cahNkF_gZWifU7IV3SIVUo/view?usp=sharing

© 2021 Mohanad Gad. All rights reserved.

Generative Art Using Neural Visual Grammars and Dual Encoders

Generative Art Using Neural Visual Grammars and Dual Encoders Arnheim 1 The original algorithm from the paper Generative Art Using Neural Visual Gramm

DeepMind 231 Jan 05, 2023
Pytorch implementation of DeepMind's differentiable neural computer paper.

DNC pytorch This is a Pytorch implementation of DeepMind's Differentiable Neural Computer (DNC) architecture introduced in their recent Nature paper:

Yuanpu Xie 91 Nov 21, 2022
source code for https://arxiv.org/abs/2005.11248 "Accelerating Antimicrobial Discovery with Controllable Deep Generative Models and Molecular Dynamics"

Accelerating Antimicrobial Discovery with Controllable Deep Generative Models and Molecular Dynamics This work will be published in Nature Biomedical

International Business Machines 71 Nov 15, 2022
Faster Convex Lipschitz Regression

Faster Convex Lipschitz Regression This reepository provides a python implementation of our Faster Convex Lipschitz Regression algorithm with GPU and

Ali Siahkamari 0 Nov 19, 2021
Code for "R-GCN: The R Could Stand for Random"

RR-GCN: Random Relational Graph Convolutional Networks PyTorch Geometric code for the paper "R-GCN: The R Could Stand for Random" RR-GCN is an extensi

PreDiCT.IDLab 31 Sep 07, 2022
IPATool-py: download ipa easily

IPATool-py Python version of IPATool! Installation pip3 install -r requirements.txt Usage Quickstart: download app with specific bundleId into DIR: p

159 Dec 30, 2022
Learning Correspondence from the Cycle-consistency of Time (CVPR 2019)

TimeCycle Code for Learning Correspondence from the Cycle-consistency of Time (CVPR 2019, Oral). The code is developed based on the PyTorch framework,

Xiaolong Wang 706 Nov 29, 2022
[ICCV2021] Learning to Track Objects from Unlabeled Videos

Unsupervised Single Object Tracking (USOT) 🌿 Learning to Track Objects from Unlabeled Videos Jilai Zheng, Chao Ma, Houwen Peng and Xiaokang Yang 2021

53 Dec 28, 2022
Retinal Vessel Segmentation with Pixel-wise Adaptive Filters (ISBI 2022)

Retinal Vessel Segmentation with Pixel-wise Adaptive Filters (ISBI 2022) Introdu

anonymous 14 Oct 27, 2022
A PyTorch implementation of the architecture of Mask RCNN

EDIT (AS OF 4th NOVEMBER 2019): This implementation has multiple errors and as of the date 4th, November 2019 is insufficient to be utilized as a reso

Sai Himal Allu 975 Dec 30, 2022
Denoising Diffusion Implicit Models

Denoising Diffusion Implicit Models (DDIM) Jiaming Song, Chenlin Meng and Stefano Ermon, Stanford Implements sampling from an implicit model that is t

465 Jan 05, 2023
CLNTM - Contrastive Learning for Neural Topic Model

Contrastive Learning for Neural Topic Model This repository contains the impleme

Thong Thanh Nguyen 25 Nov 24, 2022
kullanışlı ve işinizi kolaylaştıracak bir araç

Hey merhaba! işte çok sorulan sorularının cevabı ve sorunlarının çözümü; Soru= İçinde var denilen birçok şeyi göremiyorum bunun sebebi nedir? Cevap= B

Sexettin 16 Dec 17, 2022
Code for the paper "There is no Double-Descent in Random Forests"

Code for the paper "There is no Double-Descent in Random Forests" This repository contains the code to run the experiments for our paper called "There

2 Jan 14, 2022
🔥3D-RecGAN in Tensorflow (ICCV Workshops 2017)

3D Object Reconstruction from a Single Depth View with Adversarial Learning Bo Yang, Hongkai Wen, Sen Wang, Ronald Clark, Andrew Markham, Niki Trigoni

Bo Yang 125 Nov 26, 2022
Code in PyTorch for the convex combination linear IAF and the Householder Flow, J.M. Tomczak & M. Welling

VAE with Volume-Preserving Flows This is a PyTorch implementation of two volume-preserving flows as described in the following papers: Tomczak, J. M.,

Jakub Tomczak 87 Dec 26, 2022
To SMOTE, or not to SMOTE?

To SMOTE, or not to SMOTE? This package includes the code required to repeat the experiments in the paper and to analyze the results. To SMOTE, or not

Amazon Web Services 1 Jan 03, 2022
[ACM MM 2019 Oral] Cycle In Cycle Generative Adversarial Networks for Keypoint-Guided Image Generation

Contents Cycle-In-Cycle GANs Installation Dataset Preparation Generating Images Using Pretrained Model Train and Test New Models Acknowledgments Relat

Hao Tang 67 Dec 14, 2022
Explainability of the Implications of Supervised and Unsupervised Face Image Quality Estimations Through Activation Map Variation Analyses in Face Recognition Models

Explainable_FIQA_WITH_AMVA Note This is the official repository of the paper: Explainability of the Implications of Supervised and Unsupervised Face I

3 May 08, 2022
MG-GCN: Scalable Multi-GPU GCN Training Framework

MG-GCN MG-GCN: multi-GPU GCN training framework. For more information, please read our paper. After cloning our repository, run git submodule update -

Translational Data Analytics (TDA) Lab @GaTech 6 Oct 24, 2022