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Amir Atapour-Abarghouei's Projects

chroma-keying icon chroma-keying

a set of simple excercises in colour filtering from a live video image (inc. invisibility cloaking)

depth-hole-prediction icon depth-hole-prediction

This repository contains code for training and testing a model used to predict where holes would appear in a depth image based on an RGB image input.

depthcomp icon depthcomp

A real-time depth filling approach based on prior image segmentation (http://www.atapour.co.uk/papers/BMVC2017.pdf).

dl-pytorch icon dl-pytorch

Examples and code demonstrations for the Deep Learning module at Durham University

invisible-me icon invisible-me

This repo contains a set of simple excercises in colour filtering from a live video image. The demo will lead to the implementation of a simple "cloak of invisibility".

ip-python-opencv icon ip-python-opencv

Examples and code demonstrations for the Image Processing module at Durham University

keras-dl-examples icon keras-dl-examples

Examples and demonstration written in Python and Keras used in the "Deep Learning" lecture series at Newcastle University (CSC8637).

monoculardepth-inference icon monoculardepth-inference

Inference pipeline for the CVPR paper entitled "Real-Time Monocular Depth Estimation using Synthetic Data with Domain Adaptation via Image Style Transfer" (http://atapour.co.uk/papers/atapour18monocular.pdf).

rank-over-class icon rank-over-class

Source code for the training pipeline of the text ranking model used in the paper entitled "Rank over Class: The Untapped Potential of Ranking in Natural Language Processing" (https://arxiv.org/abs/2009.05160).

ransomware-classification icon ransomware-classification

Training and testing pipeline for ransomware classification based on screenshots of the splash screens or ransom notes (https://arxiv.org/pdf/1908.06750.pdf).

temporal-depth-segmentation icon temporal-depth-segmentation

Source code (train/test) accompanying the paper entitled "Veritatem Dies Aperit - Temporally Consistent Depth Prediction Enabled by a Multi-Task Geometric and Semantic Scene Understanding Approach" in CVPR 2019 (https://arxiv.org/abs/1903.10764).

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