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

Superpixel Sampling Networks (ECCV2018)

Implementation of Image Processing Segmentation techniques and algorithms for Oil Spill detection in SAR images

Python implementation of LSC algorithm, (C) Zhengqin Li, Jiansheng Chen, 2014

Codes for our paper "Boundary-Enhanced Self-Supervised Learningfor Brain Structure Segmentation"

HERS Superpixels: Deep Affinity Learning for Hierarchical Entropy Rate Segmentation

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:

HPCDL [Remote Sensing 2025]

SGML: A Symmetric Graph Metric Learning Framework for Efficient Hyperspectral Image Classification, JSTARS, 2021

The work presented explains how to segment the brain tumour area in absence of interaction with user basing his technique on a saliency map constructed from three different resonance techniques.

Simple Linear Iterative Clustering C# .NET Framework

Bayesian-Inspired Space-Time Superpixels

Basic implementation of SLIC algorithm for generating superpixels.

Segmentation network using superpixels and zoom-out features

Unofficial python implementation of the paper "Lazy Random Walks for Superpixel Segmentation"

This project provides an interactive GUI tool to accelerate image annotation by leveraging superpixel segmentation. It uses SLIC-based superpixels to divide images into coherent regions, enabling users to label entire segments instead of individual pixels, significantly reducing annotation time and effort.

Codes to compute Turbopixels/Turbovoxels and other related tools

FastSLIC implementation written in Rust

A cutting-edge toolkit engineered for high-precision image segmentation using Boykov-Kolmogorov algorithm and CIDE2000 formula

SLIC (Simple Linear Iterative Clustering) Superpixels for pixel clustering and segmentation