jacobs-university Goto Github PK

-icip-2-compressed-image-quality-assessment-based-on-saak-featuresfile.

adaptive-image-downscaling-public-

berlin-transportation-app-backend

berlin-transportation-app-frontend

computer-networks

Computer Networks Course 2020

emotion_recognition_photo_editor

A fun photo editing experience that does emotion detection and live speech to text to achieve some funky results!

eyden-tracer-01

Computer Graphics, Fall Semester 2019, Practical Assignment 1

eyden-tracer-02

Computer Graphics, Fall Semester 2019, Practical Assignment 2

eyden-tracer-03

Computer Graphics, Fall Semester 2019, Practical Assignment 3

eyden-tracer-04

Computer Graphics, Fall Semester 2019, Practical Assignment 4

eyden-tracer-05

Computer Graphics, Fall Semester 2019, Practical Assignment 5

eyden-tracer-06

Computer Graphics, Fall Semester 2020, Practical Assignment 6

frequent

A utility for crawling websites and building frequency lists of words

hci_chat-application

Final Project submission for HCI by (Adnan Abu Ramadan and Alex Tretyakov)

iccv---amass---archive-of-motion-iccv---amass---archive-of-motion-capture-as-surface-shapes

Deep Learning Computer Vision models depend on massive datasets for their advance computations. There are multiple human motion capture datasets available which serves the purpose of doing the base computations but lack to be the ideal dataset in two major ways. Either, the datasets are very small and are constrained to only particular motion or the output generated by these datasets is not natural, that is, it’s not true to our humane movements. These problems are solved by AMASS (Archive of Motion Capture as Surface Shapes) which generates highly versatile SMPL (Multi Person Linear Model) model outputs which includes standard skeletal representation and a full surface body mesh. The MoSh algorithm which is used to generate the output is modified to incorporate the soft tissue dynamics and renamed to MoSh++. The dataset is then made richer by adding data from datasets like DMPL (Dynamic SMPL) and MANO (Hand Model with Articulated and Non-rigid Deformations). AMASS is able to generate output which is compatible with recent graphics engines, game engines and animations requirements.

iccv1-implementation

Final project or paper implementation of course "Data Visualisation and Image Processing"

iccv1-pixel-difference-networks-for-efficient-edge-detection

iccv2--real-time-vanishing-point-detector-integrating-under-parameterized-ransac-and-hough-transform

Vanishing Point Detector Integrating Under-parameterized RANSAC and Hough Transform

iccv3-project

iccv3_salient_object

ICCV 3 - Scene Context-Aware Salient Object Detection

iccv4_imagedehazing

Image Dehazing using Convolutional Neural Networks

iccv5-prvs-image-inpainting

icip-3

icip-5-learning_to_render_better_image_previews

icip1_quarter_laplacian

icip2-hyperspectral-image-denoising-with-log-based-robust-pca

icip6-underwater-image-synthesis

miniml-01

mixed-reality-with-opencv-and-three.js

multi-color-balance-for-color-constancy

ICIP 3 - MULTI-COLOR BALANCE FOR COLOR CONSTANCY Project