There are 3 repositories under fcn topic.
A Keras port of Single Shot MultiBox Detector
PyTorch Implementation of Fully Convolutional Networks. (Training code to reproduce the original result is available.)
Tensorflow implementation of Fully Convolutional Networks for Semantic Segmentation (http://fcn.berkeleyvision.org)
A Kitti Road Segmentation model implemented in tensorflow.
Tensorflow implementation of Automatic Portrait Matting on paper "Automatic Portrait Segmentation for Image Stylization"
Pixel-wise segmentation on VOC2012 dataset using pytorch.
PytorchAutoDrive: Segmentation models (ERFNet, ENet, DeepLab, FCN...) and Lane detection models (SCNN, PRNet, RESA, LSTR, BézierLaneNet...) based on PyTorch with fast training, visualization, benchmarking & deployment help
Chainer Implementation of Fully Convolutional Networks. (Training code to reproduce the original result is available.)
Implemention of FCN-8 and FCN-16 with Keras and uses CRF as post processing
Get started with Semantic Segmentation based on Keras, including FCN32/FCN8/SegNet/U-Net
PyTorch Implementation of Fully Convolutional Networks (a very simple and easy demo).
ResUNet, a semantic segmentation model inspired by the deep residual learning and UNet. An architecture that take advantages from both(Residual and UNet) models.
This repository contains the code of HyperDenseNet, a hyper-densely connected CNN to segment medical images in multi-modal image scenarios.
UNet is a fully convolutional network(FCN) that does image segmentation. Its goal is to predict each pixel's class. It is built upon the FCN and modified in a way that it yields better segmentation in medical imaging.
CVPR2022 (Oral) - Rethinking Semantic Segmentation: A Prototype View
The code includes all the file that you need in the training stage for FCN
Tensorflow implementation : U-net and FCN with global convolution
A Python Library for High-Level Semantic Segmentation Models based on TensorFlow and Keras with pretrained backbones.
Edge-aware U-Net with CRF-RNN layer for Medical Image Segmentation
segmentation repo using pytorch
Udacity Self-Driving Car Engineer Nanodegree. Project: Road Semantic Segmentation
Tensorflow 2 implementation of complete pipeline for multiclass image semantic segmentation using UNet, SegNet and FCN32 architectures on Cambridge-driving Labeled Video Database (CamVid) dataset.
Lots of semantic image segmentation implementations in Tensorflow/Keras
[ICCV 2015] Framework for optimizing CNNs with linear constraints for Semantic Segmentation
Pytorch implementation of FCN, UNet, PSPNet, and various encoder models.
Framework for estimating temporal properties of music tracks.
GoogLeNet implementation of Fully Convolutional Networks for Semantic Segmentation in TensorFlow
Repository containing the source code of the IVD-Net segmentation network that we proposed for the MICCAI 2018 IVD segmentation challenge.
Fully Convolutional Networks for Portrait Matting
PyTorch implementation for Semantic Segmentation, include FCN, U-Net, SegNet, GCN, PSPNet, Deeplabv3, Deeplabv3+, Mask R-CNN, DUC, GoogleNet, and more dataset
FCN for Semantic Image Segmentation achieving 68.5 mIoU on PASCAL VOC
Spectral-Spatial Fully Convolutional Networks for Hyperspectral Image Classification
[SAIN'18] [Caffe] A dilated version of FCN with Stride 2 for Efficient Semantic Segmentation
Semantic segmentation for classifying road. "Fully Convolutional Networks for Semantic Segmentation (2015)" implemented using TF