Human segmentation models, training/inference code, and trained weights, implemented in PyTorch

TensorFlow-based implementation of "ICNet for Real-Time Semantic Segmentation on High-Resolution Images".

Keras-Semantic-Segmentation

ICNet and PSPNet-50 in Tensorflow for real-time semantic segmentation

ICNet implemented by pytorch, for real-time semantic segmentation on high-resolution images, mIOU=71.0 on cityscapes, single inference time is 19ms, FPS is 52.6.

Semantic segmentation task for ADE20k & cityscapse dataset, based on several models.

This repository contains UNet and ICNet implementations for semantic segmentation of nuclei images, from Kaggle's 2018 Data Science Bowl

No description provided.

ICNet for Real-Time Semantic Segmentation on High-Resolution Images

Implementation of ICNet by chainer

🚦 Train and evaluate semantic segmentation models on the Cityscapes dataset using PyTorch with DeepLabV3/DeepLabV3+ for precise pixel-wise predictions.