real-time fire detection in video imagery using a convolutional neural network (deep learning) - from our ICIP 2018 paper (Dunnings / Breckon) + ICMLA 2019 paper (Samarth / Bhowmik / Breckon)

An extensive evaluation and comparison of 28 state-of-the-art superpixel algorithms on 5 datasets.

Image segmentation - general superpixel segmentation & center detection & region growing

Superpixel Sampling Networks (ECCV2018)

Library containing 7 state-of-the-art superpixel algorithms with a total of 9 implementations used for evaluation purposes in [1] utilizing an extended version of the Berkeley Segmentation Benchmark.

20x Real-time superpixel SLIC Implementation with CPU

Learning Superpixels with Segmentation-Aware Affinity Loss

PyTorch code for our BMVC 2019 paper "Image Classification with Hierarchical Multigraph Networks"

Image processing Toolkit in R

Implementation of the superpixel algorithm called SEEDS [1].

Implementation of efficient graph-based image segmentation as proposed by Felzenswalb and Huttenlocher [1] that can be used to generate oversegmentations.

Extended version of the Berkeley Segmentation Benchmark [1] used for evaluation in [2].

Simple linear iterative clustering (SLIC) in a region of interest (ROI)

[TIP 2023] The official repo for the paper "DCN-T: Dual Context Network with Transformer for Hyperspectral Image Classification".

A set of algorithms and other cool things that I learned while doing image processing with openCV using C++ and python.

Superpixels segmentation algorithms with QT and OpenCV, with a nice GUI to colorize the cells

Superpixel-based Refinement for Object Proposal Generation (ICPR 2020)

Benchmarking GNNs with PyTorch Lightning: Open Graph Benchmarks and image classification from superpixels

Augmentations for Neural Networks. Implementation of Torchvision's transforms using OpenCV and additional augmentations for super-resolution, restoration and image to image translation.

Official implementation of "Minimizing Supervision for Free-space Segmentation" paper