FgSegNet: Foreground Segmentation Network, Foreground Segmentation Using Convolutional Neural Networks for Multiscale Feature Encoding

Simplified Deep Image Matting training code with keras on tensorflow

Adaptive foreground-background segmentation using Gaussian Mixture Models (GMMs)

Python-based OpenCV program for detecting leaves and creating segmentation masks based on images in the Komatsuna dataset.

PyTorch Implementation for Segmentation and Saliency Prediction

Unsupervised, one-shot, instance-based active contour/snake using deep learning features in python.

My additions to the state of the art foreground extraction method by Long Ang LIM and Hacer YALIM KELES. The original paper can be found at the link below.

End-to-end CNN-based Autoencoder that can segment any objects even if it is out of the classes present in the training set.

使用onnxruntime部署微软发布的DAViD：深度估计、表面法线估计和软前景分割，包含C++和Python两个版本的程序

Term project for my NCTU course "Image-based Modeling and Rendering"

An official repository for "Background subtraction based on Gaussian mixture models using color and depth information".

Implementation of algorithm for foreground-background separation in low quality patrimonial document images.

Final Project of Advanced Data Structure and Algorithm

Foreground and background segmentation using OpenCV and C++

Implement a basic version of the interactive image cut-out/segmentation approach called Lazy Snapping. The program uses K-Means Clustering to segment images into foreground and background based on user-provided seed pixels.