There are 63 repositories under semantic-segmentation topic.
A CNN based image segmentation tool oriented to marine data analysis
Fully Convolutional Networks for Portrait Matting
PyTorch implementation for Semantic Segmentation, include FCN, U-Net, SegNet, GCN, PSPNet, Deeplabv3, Deeplabv3+, Mask R-CNN, DUC, GoogleNet, and more dataset
A framework for annotating 3D meshes using the predictions of a 2D semantic segmentation model.
FCN for Semantic Image Segmentation achieving 68.5 mIoU on PASCAL VOC
Boundary-Aware Feature Propagation for Scene Segmentation (ICCV2019)
🍔🍟🍗 Food analysis baseline with Theseus. Integrate object detection, image classification and multi-class semantic segmentation. 🍞🍖🍕
Real-time CPU person segmentation for privacy in video calls
Implementation details for EDANet
AttaNet for real-time semantic segmentation.
Implementation of CCNet: Criss-Cross Attention for Semantic Segmentation
[CVPR 2022] Self-supervised Image-specific Prototype Exploration for Weakly Supervised Semantic Segmentation
Semantic Segmentation PyTorch code for our paper: Pyramidal Convolution: Rethinking Convolutional Neural Networks for Visual Recognition (https://arxiv.org/pdf/2006.11538.pdf)
:sunglasses: A curated list of domain adaptation papers, datasets and other resources.
[TGRS 2021] FactSeg: Foreground Activation Driven Small Object Semantic Segmentation in Large-Scale Remote Sensing Imagery
U-NET Semantic Segmentation model for Mobile
Label-Pixels is a tool for semantic segmentation of remote sensing images using fully convolutional networks (FCNs), designed for extracting the road network from remote sensing imagery and it can be used in other applications applications to label every pixel in the image ( Semantic segmentation).
Summary of RGBT SOD and SS.
A PyTorch implementation of semantic segmentation according to Multi-Scale Context Aggregation by Dilated Convolutions by Yu and Koltun.
Building footprint segmentation from satellite and aerial imagery
PyTorch U-Net on Cityscapes Dataset
InstantDL: An easy and convenient deep learning pipeline for image segmentation and classification
Semantic Understanding of Foggy Scenes with Purely Synthetic Data
This is a repository for a semantic segmentation inference API using the OpenVINO toolkit
Car parts dataset for object detection and semantic segmentation tasks, provided by DSMLR lab, IT-KMITL.
A collection of easy-to-use image/video filter.
[SAIN'18] [Caffe] A dilated version of FCN with Stride 2 for Efficient Semantic Segmentation
Code for the paper 'Skin Segmentation from NIR Images using Unsupervised Domain Adaptation through Generative Latent Search'. Accepted in ECCV2020 (Spotlight). Preprint: https://arxiv.org/abs/2006.08696
Official re-implementation of the Calibrated Adversarial Refinement model described in the paper "Calibrated Adversarial Refinement for Stochastic Semantic Segmentation"
Cell Detection with PyTorch.
Code for the paper: Valvano G. et al. (2021), Learning to Segment from Scribbles using Multi-scale Adversarial Attention Gates
CV integrated project. Including MOT to track cars and pedestrians, object detection and image classification to get license plate content, semantic segmentation to get zebra crossing, tradition method to get area of lanes .etc.
[cvpr22] Perturbed and Strict Mean Teachers for Semi-supervised Semantic Segmentation
A PyTorch Implementation of Fast-SCNN: Fast Semantic Segmentation Network(PyTorch >= 1.4)