Papers with Code 아카이브
Autonomous Vehicles
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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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/kaseris/ILSVRCPlus
https://github.com/katieluo88/280finalproj_nyudepth
Sparse-to-Dense: Depth Prediction from Sparse Depth Samples and a Single Image
https://github.com/katieluo88/drift
Reward Finetuning for Faster and More Accurate Unsupervised Object Discovery
https://github.com/kaustavsenkvs/Deep-Learning-Mini-Project
https://github.com/kav-institute/mdn_trajectory_forecasting
https://github.com/kawshik8/DL-project
https://github.com/kaycee-agent/End-to-End-Self-Driving-via-CNN
https://github.com/kazuki-shin/l5kit
One Thousand and One Hours: Self-driving Motion Prediction Dataset
https://github.com/kbrodt/waymo-motion-prediction-2021
MotionCNN: A Strong Baseline for Motion Prediction in Autonomous Driving
https://github.com/kclip/localized-adaptive-risk-control
https://github.com/ken-power/SelfDrivingCarND-ExtendedKalmanFilter
No Blind Spots: Full-Surround Multi-Object Tracking for Autonomous Vehicles using Cameras & LiDARs
https://github.com/ken-power/SensorFusionND-3D-Object-Tracking
No Blind Spots: Full-Surround Multi-Object Tracking for Autonomous Vehicles using Cameras & LiDARs
https://github.com/kentttttt/darknet
https://github.com/keras-team/keras-applications
https://github.com/kfragkedaki/pedestrian_project
https://github.com/khaled2ahmed/k2a
https://github.com/khalidw/MOT16_Annotator
MOTChallenge 2015: Towards a Benchmark for Multi-Target Tracking
https://github.com/khanh-moriaty/DarknetAlexey
https://github.com/khlaifiabilel/Autonomous-UAV-visual-navigation
https://github.com/kingcong/densenet
https://github.com/kingcong/gpu_FaceAttribute
https://github.com/kingcong/gpu_SE-Net
https://github.com/kingcong/resnet
https://github.com/kingjamessong/rankfeat
Scaling Out-of-Distribution Detection for Real-World Settings
https://github.com/kinglintianxia/KittiSeg
MultiNet: Real-time Joint Semantic Reasoning for Autonomous Driving
https://github.com/kinglintianxia/MultiNet
MultiNet: Real-time Joint Semantic Reasoning for Autonomous Driving
https://github.com/kiranu1024/deep-learning
https://github.com/kirilcvetkov92/Self-Driving-Car-Behavior-Deep-Learning
https://github.com/kiruthick101/darknet
https://github.com/kishanAk21/Skin-Cancer-Image-Classification
https://github.com/kishorkuttan/traffic_net
https://github.com/kisna-aryan/YOLOX
https://github.com/kit-mrt/road-barlow-twins
MotionCNN: A Strong Baseline for Motion Prediction in Autonomous Driving
https://github.com/kjboggess/ijcai23
Toward Policy Explanations for Multi-Agent Reinforcement Learning
https://github.com/klintan/pytorch-lanenet
Towards End-to-End Lane Detection: an Instance Segmentation Approach
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.