Implementation of gaze tracking and demo

Last update: Oct 20, 2022

Related tags

Deep Learning GazeDetection_AI

Overview

Predicting Customer Demand by Using Gaze Detecting and Object Tracking

This project is the integration of gaze detecting and object tracking.

Predict the gaze location and find out what object the user is looking at.

Getting started

Using Node.js to display this work

cd GazeDemo_Web

Create .env file to save your database access info and import project.sql file to your schema.

.env
```
PORT=3000

DB_HOST=localhost
DB_USER=root
DB_PASS= *YOUR PASSWORD*
DB_NAME=project
```
npm install
node . or nodemon

To run server

Calibration

Demo

Customized video

It needs only a youtube link to upload and use your own video.

Owner

GitHub Repository

Official Repository of NeurIPS2021 paper: PTR

PTR: A Benchmark for Part-based Conceptual, Relational, and Physical Reasoning Figure 1. Dataset Overview. Introduction A critical aspect of human vis

32 Jun 02, 2022

Rethinking Portrait Matting with Privacy Preserving

Rethinking Portrait Matting with Privacy Preserving This is the official repository of the paper Rethinking Portrait Matting with Privacy Preserving.

184 Jan 03, 2023

Rank 3 : Source code for OPPO 6G Data Generation Challenge

OPPO 6G Data Generation with an E2E Framework Homepage of OPPO 6G Data Generation Challenge Datasets H1_32T4R.mat H2_32T4R.mat Please put the original

97 Jan 07, 2023

This is a classifier which basically predicts whether there is a gun law in a state or not, depending on various things like murder rates etc.

Gun-Laws-Classifier This is a classifier which basically predicts whether there is a gun law in a state or not, depending on various things like murde

1 Jan 20, 2022

Temporally Coherent GAN SIGGRAPH project.

TecoGAN This repository contains source code and materials for the TecoGAN project, i.e. code for a TEmporally COherent GAN for video super-resolution

2 Jan 18, 2022

Self-supervised Label Augmentation via Input Transformations (ICML 2020)

Self-supervised Label Augmentation via Input Transformations Authors: Hankook Lee, Sung Ju Hwang, Jinwoo Shin (KAIST) Accepted to ICML 2020 Install de

96 Dec 29, 2022

Latte: Cross-framework Python Package for Evaluation of Latent-based Generative Models

Cross-framework Python Package for Evaluation of Latent-based Generative Models Latte Latte (for LATent Tensor Evaluation) is a cross-framework Python

30 Sep 08, 2022

A Vision Transformer approach that uses concatenated query and reference images to learn the relationship between query and reference images directly.

24 Dec 13, 2022

LibMTL: A PyTorch Library for Multi-Task Learning

LibMTL LibMTL is an open-source library built on PyTorch for Multi-Task Learning (MTL). See the latest documentation for detailed introductions and AP

765 Jan 06, 2023

Rational Activation Functions - Replacing Padé Activation Units

Rational Activations - Learnable Rational Activation Functions First introduce as PAU in Padé Activation Units: End-to-end Learning of Activation Func

[email protected]"> 38 Nov 22, 2022

Implementation of PersonaGPT Dialog Model

PersonaGPT An open-domain conversational agent with many personalities PersonaGPT is an open-domain conversational agent cpable of decoding personaliz

42 Jan 01, 2023

CNNs for Sentence Classification in PyTorch

Introduction This is the implementation of Kim's Convolutional Neural Networks for Sentence Classification paper in PyTorch. Kim's implementation of t

956 Dec 19, 2022

Tutel MoE: An Optimized Mixture-of-Experts Implementation

Project Tutel Tutel MoE: An Optimized Mixture-of-Experts Implementation. Supported Framework: Pytorch Supported GPUs: CUDA(fp32 + fp16), ROCm(fp32) Ho

344 Dec 29, 2022

PyTorch implementation of the paper Ultra Fast Structure-aware Deep Lane Detection

1.4k Jan 06, 2023

Is RobustBench/AutoAttack a suitable Benchmark for Adversarial Robustness?

Adversrial Machine Learning Benchmarks This code belongs to the papers: Is RobustBench/AutoAttack a suitable Benchmark for Adversarial Robustness? Det

9 Nov 27, 2022

Implementation of DropLoss for Long-Tail Instance Segmentation in Pytorch

[AAAI 2021]DropLoss for Long-Tail Instance Segmentation [AAAI 2021] DropLoss for Long-Tail Instance Segmentation Ting-I Hsieh*, Esther Robb*, Hwann-Tz

37 Dec 02, 2022

In this repo we reproduce and extend results of Learning in High Dimension Always Amounts to Extrapolation by Balestriero et al. 2021

In this repo we reproduce and extend results of Learning in High Dimension Always Amounts to Extrapolation by Balestriero et al. 2021. Balestriero et

1 Jan 27, 2022