OpenMMLab Semantic Segmentation Toolbox and Benchmark.

🤘 awesome-semantic-segmentation

The repository contains source code and models to use PixelNet architecture used for various pixel-level tasks. More details can be accessed at <http://www.cs.cmu.edu/~aayushb/pixelNet/>.

PyTorch implementation of deep learning models on materials microscopic image datasets

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.

PyTorch implementation of PSPNet segmentation network

Pytorch code for semantic segmentation using ERFNet

Pytorch implementation of GCN architecture for semantic segmentation

PyTorch implementation of DeepLabv3

Pretrained DeepLabv3 and DeepLabv3+ for Pascal VOC & Cityscapes

Codebase and pretrained models for ECCV'18 Unified Perceptual Parsing

PyTorch implementation of Non-Local Neural Networks (https://arxiv.org/pdf/1711.07971.pdf)

Dual Attention Network for Scene Segmentation (CVPR2019)

Adaptive Pyramid Context Network for Semantic Segmentation (APCNet CVPR'2019)

The code for Expectation-Maximization Attention Networks for Semantic Segmentation (ICCV'2019 Oral)

GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond

CCNet: Criss-Cross Attention for Semantic Segmentation (TPAMI 2020 & ICCV 2019).

Dynamic Multi-scale Filters for Semantic Segmentation (DMNet ICCV'2019)

Learning to Adapt Structured Output Space for Semantic Segmentation, CVPR 2018 (spotlight)

Pytorch implementation of U-Net, R2U-Net, Attention U-Net, and Attention R2U-Net.

[ICCV 2023] MARS: Model-agnostic Biased Object Removal without Additional Supervision for Weakly-Supervised Semantic Segmentation

Code for CVPR 2022 paper "Multi-Class Token Transformer for Weakly Supervised Semantic Segmentation"