Semantic Segmentation on PyTorch (include FCN, PSPNet, Deeplabv3, Deeplabv3+, DANet, DenseASPP, BiSeNet, EncNet, DUNet, ICNet, ENet, OCNet, CCNet, PSANet, CGNet, ESPNet, LEDNet, DFANet)

Source Code of our CVPR2021 paper "Rethinking BiSeNet For Real-time Semantic Segmentation"

Semantic Segmentation in Pytorch. Network include: FCN、FCN_ResNet、SegNet、UNet、BiSeNet、BiSeNetV2、PSPNet、DeepLabv3_plus、 HRNet、DDRNet

BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation | Face Parsing | In PyTorch >> ONNX Runtime Inference

Unofficial tensorflow implementation of real-time scene image segmentation model "BiSeNet V2: Bilateral Network with Guided Aggregation for Real-time Semantic Segmentation"

Keras BiseNet architecture implementation

BiSeNet--Bilateral-Segmentation-Network-for-Real-time-Semantic-Segmentation论文代码

Paddle version of STDCNet for paper“Rethinking BiSeNet For Real-time Semantic Segmentation”

BiSeNet for semantic segmentation task

BiSeNet v2 RGB Semantic Segmentation + Depth map input

training and evaluation of BiSeNet and DeepLab models to address the domain shift problem in semantic segmentation

semantic segmentation on camvid using BiSeNet

reproduceing semantic segmentation based on bisenet

BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation

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utilization of BiSeNet and DeepLabV2 models for real-time semantic segmentation

Paddle复现论文Rethinking BiSeNet For Real-time Semantic Segmentation

A Cog implementation of BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation [Face Parsing]

Unofficial implementation of BiSeNet V2: Bilateral Network with Guided Aggregation for Real-time Semantic Segmentation https://arxiv.org/pdf/2004.02147.pdf

Project for "Advanced Machine Learning" course at PoliTO. The purpose is to implement a BiSeNet able to perform real-time semantic segmentation task

Report of the project for the course of Machine Learning and Deep Learning. Assignment on Semantic Segmentation: A Comparative Study on DeepLabV2, BiSeNet, PIDNet

Real-time domain adaptation for semantic segmentation using BiSeNet on GTA5 → Cityscapes, featuring FDA, DACS, and a hybrid CrossEntropy + Dice loss extension for class imbalance.