There are 6 repositories under real-time-semantic-segmentation topic.
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.)
Source Code of our CVPR2021 paper "Rethinking BiSeNet For Real-time Semantic Segmentation"
CFPNet-M: A Light-Weight Encoder-Decoder Based Network for Multimodal Biomedical Image Real-Time Segmentation
Unofficial tensorflow implementation of real-time scene image segmentation model "BiSeNet V2: Bilateral Network with Guided Aggregation for Real-time Semantic Segmentation"
Panoramic Annular Semantic Segmentation
Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes
[ICCV 2021] FaPN: Feature-aligned Pyramid Network for Dense Image Prediction
ERF-PSPNET implemented by tensorflow
Scale-ware Strip Attention Guided Feature Pyramid Network for Real-time Semantic Segmentation
First implementation of PIDNet in Tensorflow/Keras.
Official implementation of TransNetR: Transformer-based Residual Network for Polyp Segmentation with Multi-Center Out-of-Distribution Testing (MIDL 2022)
Pytorch code of Sequential/Hierarchical ERFNet with PSPNet for real-time semantic segmentation
BiSeNetV2 implementation in TensorFlow 2.0
Detail-Sensitive Panoramic Annular Semantic Segmentation
DSANet: Dilated Spatial Attention for Real-time Semantic Segmentation in Urban Street Scenes
Pytorch Implementation of ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation (https://arxiv.org/abs/1606.02147)
Oil Pollution Dataset and PIDNet
Image Segmentation Paper Review and Implementation
Implement a model of real-time semantic segmentation for autonomous driving
Improved PIDNet for real-time semantic segmentation. Work in progress.
[ICIP2022] Entropy guided feature extraction for real time semantic segmentation
:basketball: BasketballDetector implementation using a segmentation approach
This repository contains research on real-time domain adaptation in semantic segmentation, aiming at bridging the gap between synthetic and real-world imagery for urban scenes and autonomous driving, utilizing STDC models and advanced domain adaptation methods.
Project for the Advanced Machine Learning course 23/24 - Politecnico di Torino
A class-based styling approach for Real-time Domain Adaptation in Semantic Segmentation
Implementation of a Deep Neural Architecture to perform real-time semantic segmentation of forest fires in aerial imagery captured by drones.
Project for "Advanced Machine Learning" course at PoliTO. The purpose is to implement a BiSeNet able to perform real-time semantic segmentation task
Navigation based on semantic segmentation of images.
This work explores adversarial domain adaptation to enhance real-time neural networks for semantic segmentation, specifically addressing the challenges of domain shift from synthetic to real-world environments.