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/ThomasDupiereux/hpgan
https://github.com/Tiago-Roxo/Faces-in-the-Wild
YinYang-Net: Complementing Face and Body Information for Wild Gender Recognition
https://github.com/Tiago-Roxo/YinYang-Net
YinYang-Net: Complementing Face and Body Information for Wild Gender Recognition
https://github.com/TianXiaoRui/Monocular_DXSLAM
DXSLAM: A Robust and Efficient Visual SLAM System with Deep Features
https://github.com/TianmingQiu/HydraPlusNet
HydraPlus-Net: Attentive Deep Features for Pedestrian Analysis
https://github.com/TimVerion/lanenet-lane-detection-master
Towards End-to-End Lane Detection: an Instance Segmentation Approach
https://github.com/Tinker-Twins/Behavioral-Cloning-Simulator
Robust Behavioral Cloning for Autonomous Vehicles using End-to-End Imitation Learning
https://github.com/TonghanWang/NDQ
https://github.com/ToniRV/Kimera-VIO-Evaluation
Incremental Visual-Inertial 3D Mesh Generation with Structural Regularities
https://github.com/Tony363/Teamplay_Yolov3
https://github.com/TornikeAm/Semantic-Segmentation-on-Pascal-VOC
https://github.com/TowardHumanizedInteraction/TripletFace
https://github.com/TraffiX-VideoQA/TUMTraffic-VideoQA-Baseline
TUMTraffic-VideoQA: A Benchmark for Unified Spatio-Temporal Video Understanding in Traffic Scenes
https://github.com/TravisTorch/Pytorch
https://github.com/TrustAI/AdversarialDriving
Adversarial Driving: Attacking End-to-End Autonomous Driving
https://github.com/TsingZ0/PFL-Non-IID
FedBN: Federated Learning on Non-IID Features via Local Batch Normalization
https://github.com/Tsinghua-MARS-Lab/HDMapNet
HDMapNet: An Online HD Map Construction and Evaluation Framework
https://github.com/Tsinghua-MARS-Lab/vectormapnet
https://github.com/TuSimple/RangeDet
Range Conditioned Dilated Convolutions for Scale Invariant 3D Object Detection
https://github.com/Turoad/lanedet
Spatial As Deep: Spatial CNN for Traffic Scene Understanding
https://github.com/TurtleZhong/AVP-SLAM-SIM
AVP-SLAM: Semantic Visual Mapping and Localization for Autonomous Vehicles in the Parking Lot
https://github.com/TusharMhaske28/Object-Detection
https://github.com/TusharMhaske28/Thermal-Object
https://github.com/TusharMhaske28/summer-project
https://github.com/UESBTC/DenseNet-Tensorflow
https://github.com/UMich-BipedLab/automatic_lidar_camera_calibration
https://github.com/UMich-BipedLab/extrinsic_lidar_camera_calibration
https://github.com/UMich-BipedLab/sync_lidartag_apriltag
https://github.com/UnofficialJuliaMirror/DeepMark-deepmark
https://github.com/UnofficialJuliaMirrorSnapshots/DeepMark-deepmark
https://github.com/Uuuuuuho/Pillar_on_SoC
PointPillars: Fast Encoders for Object Detection from Point Clouds
https://github.com/Vamshi399/CarND-Vehicle-Detection
https://github.com/VamsiKrishna1211/gender_age-detection
https://github.com/Vermankayak/Self-Driving-Car
https://github.com/VhalPurohit/290s
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.