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.
PytorchAutoDrive: Segmentation models (ERFNet, ENet, DeepLab, FCN...) and Lane detection models (SCNN, RESA, LSTR, LaneATT, BézierLaneNet...) based on PyTorch with fast training, visualization, benchmarking & deployment help
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Tensorflow implementation of Automatic Portrait Matting on paper "Automatic Portrait Segmentation for Image Stylization"
Pixel-wise segmentation on VOC2012 dataset using pytorch.
ResUNet, a semantic segmentation model inspired by the deep residual learning and UNet. An architecture that take advantages from both(Residual and UNet) models.
PyTorch Implementation of Fully Convolutional Networks (a very simple and easy demo).
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
A Python Library for High-Level Semantic Segmentation Models based on TensorFlow and Keras with pretrained backbones.
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.
Tensorflow implementation : U-net and FCN with global convolution
Edge-aware U-Net with CRF-RNN layer for Medical Image Segmentation
Pytorch implementation of FCN, UNet, PSPNet, and various encoder models.
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.
Udacity Self-Driving Car Engineer Nanodegree. Project: Road Semantic Segmentation
Framework for estimating temporal properties of music tracks.
segmentation repo using pytorch
Lots of semantic image segmentation implementations in Tensorflow/Keras
红外弱小目标检测算法 Infrared Target Detection by Segmentation (Deeplearing Method)
PyTorch implementation for Semantic Segmentation, include FCN, U-Net, SegNet, GCN, PSPNet, Deeplabv3, Deeplabv3+, Mask R-CNN, DUC, GoogleNet, and more dataset
GoogLeNet implementation of Fully Convolutional Networks for Semantic Segmentation in TensorFlow
The source code of paper: Trend attention fully convolutional network for remaining useful life estimation in the turbofan engine PHM of CMAPSS dataset. Signal selection, Attention mechanism, and Interpretability of deep learning are explored.
PyTorch Lightning based training of Semantic Segmentation models