This is the official repository for our recent work: PIDNet

A pytorch-based real-time segmentation model for autonomous driving

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.

Semantic Segmentation using Tensorflow on popular Datasets like Ade20k, Camvid, Coco, PascalVoc

Applying the 100 Layer Tiramisu on the Camvid Dataset

This is the DL repository for Semantic Segmentation using U-Net model in pytorch library.

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

Pytorch Implementation of ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation (https://arxiv.org/abs/1606.02147)

Semantic segmentation on CamVid dataset using the U-Net.

Adapted representation of synthetic data to real world data.

CamVid Dataset for Segmentation

Репозиторий для обучения нейросетевых моделей по семантической сегментации + пример использования моделей на практике

This project was developed as a part of the presentation that I gave on the Programming 2.0 webinar: Autonomous driving.

Image Segmentation by Iterative Inference from Conditional Score Estimation

This is a project on semantic image segmentation using CamVid dataset, implemented through the FastAI framework.

Training a model using UNET and ResNet34 to do image segmentation on street images

Deep Convolutional Encoder-Decoder Architecture implemented along with max-pooling indices for pixel-wise semantic segmentation using CamVid dataset.

MATLAB implementation of popular image segmentation algorithms

Deep Convolutional Encoder-Decoder Architecture implemented along with max-pooling indices for pixel-wise semantic segmentation using CamVid dataset.

fast semantic segmentation with Enet