Autonomous Vehicles
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Autonomous vehicles is the task of making a vehicle that can guide itself without human conduction.
Many of the state-of-the-art results can be found at more general task pages such as 3D Object Detection and Semantic Segmentation.
<span style="color:grey; opacity: 0.6">( Image credit: GSNet: Joint Vehicle Pose and Shape Reconstruction with Geometrical and Scene-aware Supervision )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/flyyufelix/DenseNet-Keras
https://github.com/fmahoudeau/ShelfNet-Human-Pose-Estimation
https://github.com/fofore/yolov3-pyroch
https://github.com/fpthink/stnet
Model-free Vehicle Tracking and State Estimation in Point Cloud Sequences
https://github.com/fpthink/v2b
Model-free Vehicle Tracking and State Estimation in Point Cloud Sequences
https://github.com/franpin/topologic
TopoLogic: An Interpretable Pipeline for Lane Topology Reasoning on Driving Scenes
https://github.com/fredotran/traffic-sign-detector-yolov4
https://github.com/fredotran/traffic-signs-detection
https://github.com/fredotran/yolov3-opencvdnn
https://github.com/freedombenLiu/AirSim
AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehicles
https://github.com/fudan-zvg/roadnetworktransformer
https://github.com/fundamentalvision/BEVFormer
https://github.com/fxfviolet/Densenet_for_quiz_classification
https://github.com/fznsakib/great-ape-behaviour-detector
https://github.com/gaetandi/cheXpert
https://github.com/gakkifan2020/YoloV3_From_calmisential_workspace
https://github.com/gaozhitong/atta
Scaling Out-of-Distribution Detection for Real-World Settings
https://github.com/gargarchit/60DaysOfUdacity
https://github.com/garrickbrazil/AR-Ped
https://github.com/garrickbrazil/SDS-RCNN
Illuminating Pedestrians via Simultaneous Detection & Segmentation
https://github.com/gatheluck/Stronghold
https://github.com/gcr/torch-residual-networks
https://github.com/gdaosu/awesome-pointcloudregistration
https://github.com/gdineshk6174/self-driving-car
https://github.com/gdlg/panoramic-depth-estimation
https://github.com/gengshan-y/high-res-stereo
https://github.com/geodekid/frnn
Full-Resolution Residual Networks for Semantic Segmentation in Street Scenes
https://github.com/georghess/neurad
SplatAD: Real-Time Lidar and Camera Rendering with 3D Gaussian Splatting for Autonomous Driving
https://github.com/ghadahamed/darknet
https://github.com/ghaniskn/GCorp-Darknet
https://github.com/ghimiredhikura/Complex-YOLO-V3
https://github.com/ghimiredhikura/Complex-YOLOv3
https://github.com/gingkg/smac
https://github.com/gitliber/Basic_self_driving_car
https://github.com/giusenso/seld-tcn
SELD-TCN: Sound Event Localization & Detection via Temporal Convolutional Networks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.