Popular GitHub Repositories for Fcn

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

Tensorflow implementation of Automatic Portrait Matting on paper "Automatic Portrait Segmentation for Image Stylization"

Pixel-wise segmentation on VOC2012 dataset using pytorch.

CVPR2022 (Oral) - Rethinking Semantic Segmentation: A Prototype View

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

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

FCN for Semantic Image Segmentation achieving 68.5 mIoU on PASCAL VOC

A Tensorflow Implementation of Brain Tumor Segmentation using Topological Loss

Pytorch implementation(LeNet, VGGNet, GAN, UNet, Mask R-CNN, ...)

Implementation of FCN (8/16/32) in Tensorflow. :cyclone: 在TensorFlow框架下实现 FCN (全卷积神经网络) 。

2D semantic segmentation that assigns labels to multiple object categories on Potsdam dataset :rocket:

Multimodal Fully Convolutional Neural networks for Semantic Segmentation.

Lane detection using Semantic Segmentation. To be used in industries by autonomous shuttles in a controlled environment.

Deep learning semantic segmentation on the Camvid dataset using PyTorch FCN ResNet50 neural network.

a implement of FCN in Tensorflow based on human body photos

Multi-Dimensional Analysis of Hate Speech Using BERT and Cluster Analysis