There are 5 repositories under superpixels topic.
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.
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.
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)
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
Official implementation of "Minimizing Supervision for Free-space Segmentation" paper
Augmentations for Neural Networks. Implementation of Torchvision's transforms using OpenCV and additional augmentations for super-resolution, restoration and image to image translation.
Paper list
Research internship - Image segmentation by superpixels based on PyTorch
Image Segmentation using Superpixels, Affinity Propagation and Kmeans Clustering
[ICIP'19] LSTM-MA: A LSTM Method with Multi-modality and Adjacency Constraint for Brain Image Segmentation (Oral)
Implementation of Image Processing Segmentation techniques and algorithms for Oil Spill detection in SAR images
Bachelor thesis "Superpixel Segmentation using Depth Information", including a thorough comparison of several state-of-the-art superpixel algorithms.
Example of using VLFeat's SLIC implementation from C++.
Matlab scripts that implement necessary algorithmic procedures to automatically color a black and white image. In particular, you need to develop code to perform some computing activities:
HERS Superpixels: Deep Affinity Learning for Hierarchical Entropy Rate Segmentation
Semantic neural network to realize pixel-wise classification of 2D nano-material using Matlab
Image Segmentation using k-means, n-cuts and superpixels
Graph-Based Image Segmentation in Rust