Topic: drivable-area-segmentation Goto Github
Some thing interesting about drivable-area-segmentation
Some thing interesting about drivable-area-segmentation
drivable-area-segmentation,This is a course project for DSCI-6011 - Deep Learning. deals with Drivable Area and lane segmentation for self driving cars
User: balnarendrasapa
drivable-area-segmentation,Argoverse API for manipulating Argoverse 1 and Argoverse 2 Dataset for 3D Drivable Area Detection using LiDAR
User: christofel04
drivable-area-segmentation,An easy-to-use implementation for performing inferencing with TwinLiteNet model using OpenCV DNN module. TwinLiteNet is a lightweight and efficient deep learning model designed for drivable area and lane segmentation
User: harrylal
Home Page: https://github.com/chequanghuy/TwinLiteNet
drivable-area-segmentation,Perform inference with TwinLiteNet model using ONNX Runtime. TwinLiteNet is a lightweight and efficient deep learning model designed for drivable area and lane segmentation
User: harrylal
Home Page: https://github.com/chequanghuy/TwinLiteNet
drivable-area-segmentation,使用OpenCV部署HybridNets,同时处理车辆检测、可驾驶区域分割、车道线分割,三项视觉感知任务,包含C++和Python两种版本的程序实现。本套程序只依赖opencv库就可以运行, 彻底摆脱对任何深度学习框架的依赖。
User: hpc203
drivable-area-segmentation,使用OpenCV部署全景驾驶感知网络YOLOP,可同时处理交通目标检测、可驾驶区域分割、车道线检测,三项视觉感知任务,包含C++和Python两种版本的程序实现。本套程序只依赖opencv库就可以运行, 从而彻底摆脱对任何深度学习框架的依赖。
User: hpc203
drivable-area-segmentation,分别使用OpenCV、ONNXRuntime部署YOLOPV2目标检测+可驾驶区域分割+车道线分割,一共包含54个onnx模型,依然是包含C++和Python两个版本的程序。仅仅只依赖OpenCV就能运行,彻底摆脱对任何深度学习框架的依赖。
User: hpc203
drivable-area-segmentation,You Only Look Once for Panopitic Driving Perception.(MIR2022)
Organization: hustvl
drivable-area-segmentation,This is an unofficial Python demo of the Self-Supervised Label Generator (SSLG), presented in "Self-Supervised Drivable Area and Road Anomaly Segmentation using RGB-D Data for Robotic Wheelchairs. Our SSLG can be used effectively for self-supervised drivable area and road anomaly segmentation based on RGB-D data".
User: ntkhoa95
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