878 Open source projects that are alternatives of or similar to Fcn

TFslim based semantic segmentation models, modular&extensible boutique design

Sandbox for training deep learning networks

FCN for Semantic Image Segmentation achieving 68.5 mIoU on PASCAL VOC

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.

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.

PyTorch Implementation of Fully Convolutional Networks. (Training code to reproduce the original result is available.)

Source code for the MICCAI 2016 Paper "Automatic Liver and Lesion Segmentation in CT Using Cascaded Fully Convolutional NeuralNetworks and 3D Conditional Random Fields"

PyTorch implementation of the U-Net for image semantic segmentation with high quality images

Lightweight models for real-time semantic segmentationon PyTorch (include SQNet, LinkNet, SegNet, UNet, ENet, ERFNet, EDANet, ESPNet, ESPNetv2, LEDNet, ESNet, FSSNet, CGNet, DABNet, Fast-SCNN, ContextNet, FPENet, etc.)

Helper package with multiple U-Net implementations in Keras as well as useful utility tools helpful when working with image semantic segmentation tasks. This library and underlying tools come from multiple projects I performed working on semantic segmentation tasks

WMH segmentaion with unet, dilated_unet, and with ideas from denseNet

Implementation of "Automatic Portrait Segmentation" and "Deep Automatic Portrait Matting" with Chainer.

Pixel-wise segmentation on VOC2012 dataset using pytorch.

Segmentation models with pretrained backbones. PyTorch.

Tensorflow 2.3.0 implementation of DeepLabV3-Plus

Segmentation models (ERFNet, ENet, DeepLab, FCN...) and Lane detection models (SCNN, SAD, PRNet, RESA, LSTR...) based on PyTorch 1.6 with mixed precision training

常用的语义分割架构结构综述以及代码复现

Training & Quantization of embedded friendly Deep Learning / Machine Learning / Computer Vision models

SegNet implementation & experiments in Chainer

CCNet: Criss-Cross Attention for Semantic Segmentation (TPAMI 2020 & ICCV 2019).

A framework for training segmentation models in pytorch on labelme annotations with pretrained examples of skin, cat, and pizza topping segmentation

Project to train/test convolutional neural networks to extract buildings from SpaceNet satellite imageries.

Semantic Segmentation Suite in TensorFlow. Implement, train, and test new Semantic Segmentation models easily!

Semantic Segmentation PyTorch code for our paper: Pyramidal Convolution: Rethinking Convolutional Neural Networks for Visual Recognition (https://arxiv.org/pdf/2006.11538.pdf)

DL & CV & Neural Network

Summary and experiment includes basic segmentation, human segmentation, human or portrait matting for both image and video.

ResUNet, a semantic segmentation model inspired by the deep residual learning and UNet. An architecture that take advantages from both(Residual and UNet) models.

CRF-RNN PyTorch version http://crfasrnn.torr.vision

PyTorch Implementation of 2D and 3D 'squeeze and excitation' blocks for Fully Convolutional Neural Networks

BCDU-Net : Medical Image Segmentation

Pytorch code for semantic segmentation using ERFNet

Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs

segmentation paper reading notes

A Kitti Road Segmentation model implemented in tensorflow.

The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.

LightNet: Light-weight Networks for Semantic Image Segmentation (Cityscapes and Mapillary Vistas Dataset)

GoogLeNet implementation of Fully Convolutional Networks for Semantic Segmentation in TensorFlow

A native Tensorflow implementation of semantic segmentation according to Multi-Scale Context Aggregation by Dilated Convolutions (2016). Optionally uses the pretrained weights by the authors.

Official Pytorch Code of KiU-Net for Image Segmentation - MICCAI 2020 (Oral)

Get started with Semantic Segmentation based on Keras, including FCN32/FCN8/SegNet/U-Net

Tensorflow implementation of Fully Convolutional Networks for Semantic Segmentation (http://fcn.berkeleyvision.org)

🎨 🎨 深度学习 卷积神经网络教程 ：图像识别，目标检测，语义分割，实例分割，人脸识别，神经风格转换，GAN等🎨🎨 https://dataxujing.github.io/CNN-paper2/

Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers

PSPNet in Chainer

An awesome semantic segmentation model that runs in real time

The code includes all the file that you need in the training stage for FCN

segmentation repo using pytorch

Collection of computer vision models, ready to be included in a JVM project

Convolutional (Patch) Networks for Semantic Segmentation

PyTorch Implementation of Fully Convolutional Networks (a very simple and easy demo).

This repository contains the code of HyperDenseNet, a hyper-densely connected CNN to segment medical images in multi-modal image scenarios.

LightNet: Light-weight Networks for Semantic Image Segmentation (Cityscapes and Mapillary Vistas Dataset)

Binary semantic segmentation with UNet based on MobileNetV2 encoder

CNNs for semantic segmentation using Keras library

An opensource lib. for vehicle vision applications (written by MATLAB), lane marking detection, road segmentation

Implemention of FCN-8 and FCN-16 with Keras and uses CRF as post processing

The OCR approach is rephrased as Segmentation Transformer: https://arxiv.org/abs/1909.11065. This is an official implementation of semantic segmentation for HRNet. https://arxiv.org/abs/1908.07919