无人驾驶的资源列表中文版
精选无人驾驶资源列表,修改自takeitallsource/awesome-autonomous-vehicles :fire:.
除此之外,将继续跟随最新资源
希望大家自由给列表进行pull request~~
机器学习
框架、库和软件的精选列表
。 由Joseph Misiti.Joseph Misiti维护深度学习论文阅读路线图
从大纲到细节构建,从最新到最先进,从通用到特定领域,重点关注从深度学习开始的SOTA技术。 由Flood Sung维护。深度学习课程
旨在成为每个有兴趣认真学习该领域的人的起点。Stereo R-CNN
HKUST-Aerial-Robotics/Stereo-RCNN - CVPR2019
SimpleDet
tusimple/simpledet - SOTA on consumer grade hardware at large scale
PointPillars
traveller59/second.pytorch -SOTA for Birds Eye View Object Detection on KITTI Cyclists Moderate
PointRCNN
sshaoshuai/PointRCNN -
KITTI for 3D Object Detection (Cars)
: #2,Cars-Easy(AP:84.32%); #1,Cars-Moderate(AP:75.42%); #1,Cars-Hard(AP:67.86%)Complex-YOLO
AI-liu/Complex-YOLO -KITTI 3D Object Detection for cars
#2 Cars-Hard(AP:66.38%)PointNet
charlesq34/pointnet-
SOTA(Object Localization & 3D Object Detection)
:Cars、Cyclists、PedestrianSqueezeDet
BichenWuUCB/squeezeDet -SOTA for KITTI(2016)
VoxelNet
charlesq34/pointnet -
SOTA(Object Localization & 3D Object Detection)
:Cars、Cyclists、PedestrianLEDNet
xiaoyufenfei/LEDNet - 暂未released,Semantic Segmentation: Real-time(71FPS)
、Semantic Segmentation(Mean IoU 70.6%),ICIP 2019swiftnet
orsic/swiftnet -
Real-Time Semantic Segmentation on Cityscapes #9,Semantic Segmentation(Mean IoU:75.5%);#2,Real-time(Mean IoU:75.5%)
;#3,Real-time(Frame:39.9 fps)
,CVPR2019
Image-to-Image Translation
on SYNTHIA-to-CityscapesBiSeNet
ycszen/TorchSeg -
Cityscapes:#2,Real-time(Frame:65.5 Fps
);#8 (Mean IoU 78.9%
)、CamVid:#2,Mean IoU 68.7%;ECCV 2018MultiNet
MarvinTeichmann/MultiNet - SOTA for KITTI(Road Segmentation)Real-Time(76.9 fps)
、#16 for Mean IoU(63.06%),CVPR 2018
PSPNet
tensorflow/models和hszhao/PSPNet - SOTA in (Semantic Segmentation & Real-Time Semantic Segmentation)
,more detail,CVPR 2017
媒体来源,可以找到自动驾驶相关的主题、想法等等。
美国