Add bisenetv2. My implementation of BiSeNet

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

PyTorch implementation of over 30 realtime semantic segmentations models, e.g. BiSeNetv1, BiSeNetv2, CGNet, ContextNet, DABNet, DDRNet, EDANet, ENet, ERFNet, ESPNet, ESPNetv2, FastSCNN, ICNet, LEDNet, LinkNet, PP-LiteSeg, SegNet, ShelfNet, STDC, SwiftNet, and support knowledge distillation, distributed training, Optuna etc.

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

A framework for training segmentation models in pytorch on labelme annotations with pretrained examples of skin, cat, and pizza topping segmentation

Real Time Semantic Segmentation for both LIDAR & Camera using BiseNetv2 & PointPainting Fusion in Pytorch

Implementation of BiSeNet and BiSeNetV2

proof-of-concept program that detects rail-track with semantic segmentation for autonomous train system

bisenetv2优化版

效果很好的lanenet网络，主干网络基于bisenetv2并对主干网络做了修改，效果远好于bisnetv2

TensorRT实现BiSeNetV1与BiSeNetV2部署

BiSeNetV2 implementation in TensorFlow 2.0

BiSeNet V2 TensorFlow 2 Implementation capable of running on Edge TPUs

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Tensorflow Implementation of Face Parsing using BiseNetV2.

This is a project aiming at training an AI model for semantic segmentation purpose. The specific target is for extracting road segmentation from an image or a video on edge devices.

Image Segmentation Paper Review and Implementation

Implementation of PointPainting fusion algorithm [https://arxiv.org/pdf/1911.10150.pdf] for real-time point cloud semantic segmentation painting based on BiSeNetv2 [https://arxiv.org/pdf/1808.00897.pdf].

Implement a model of real-time semantic segmentation for autonomous driving

Simple implementaion with pytorch

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BisenetV2 auto training script

bisenetV2 plus on railsem 19

The ROS wrapper of BiSeNetV2 for semantic segmentaion using libtorch.

This repository provides a starter-code setup for the Real-Time Anomaly Segmentation project. It consists of the code base for training ERFNet, ENet and BiseNetV2 on the Cityscapes dataset and perform anomaly segmentation.

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