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/James-Yuichi-Sato/MLSYS-2022-Video-Pipeline
공식 코드https://github.com/Jamie725/RGBT-detection
공식 코드https://github.com/JeremyBYU/FastGaussianAccumulator
공식 코드https://github.com/JeremyBYU/OrganizedPointFilters
공식 코드https://github.com/JeremyBYU/polylidar
공식 코드https://github.com/JialeCao001/PedSurvey
공식 코드From Handcrafted to Deep Features for Pedestrian Detection: A Survey
https://github.com/Jiaolong/trajectory-prediction
공식 코드Trajectory Prediction for Autonomous Driving with Topometric Map
https://github.com/JiawangBian/sc_depth_pl
공식 코드https://github.com/JiaxiLi1/OWLed
공식 코드OWLed: Outlier-weighed Layerwise Pruning for Efficient Autonomous Driving Framework
https://github.com/JingWang18/Discriminative-Feature-Alignment
공식 코드https://github.com/JingwenWang95/DSP-SLAM
공식 코드https://github.com/JingyuanZhou/Safe_RL_Mixed_Traffic
공식 코드Enhancing System-Level Safety in Mixed-Autonomy Platoon via Safe Reinforcement Learning
https://github.com/Jinming-Su/SGNet
공식 코드https://github.com/JinnnK/BNBRLplus
공식 코드Belief Aided Navigation using Bayesian Reinforcement Learning for Avoiding Humans in Blind Spots
https://github.com/JoseLGomez/Co-training_SemSeg_UDA
공식 코드Co-Training for Unsupervised Domain Adaptation of Semantic Segmentation Models
https://github.com/JosephGesnouin/Asymmetrical-Bi-RNNs-to-encode-pedestrian-trajectories
공식 코드https://github.com/Jpvmello/traffic-light-detection-synthetic-context
공식 코드Deep traffic light detection by overlaying synthetic context on arbitrary natural images
https://github.com/JudasDie/SOTS
공식 코드https://github.com/JulianoLagana/MT3
공식 코드Next Generation Multitarget Trackers: Random Finite Set Methods vs Transformer-based Deep Learning
https://github.com/Jumponthemoon/WeatherDG
공식 코드https://github.com/Jumponthemoon/WeatherEdit
공식 코드WeatherEdit: Controllable Weather Editing with 4D Gaussian Field
https://github.com/JunweiLiang/Multiverse
공식 코드The Garden of Forking Paths: Towards Multi-Future Trajectory Prediction
https://github.com/JzHuai0108/kalibr
공식 코드Continuous-Time Spatiotemporal Calibration of a Rolling Shutter Camera---IMU System
https://github.com/KPeng9510/MASS
공식 코드MASS: Multi-Attentional Semantic Segmentation of LiDAR Data for Dense Top-View Understanding
https://github.com/KaimingHe/resnet-1k-layers
공식 코드https://github.com/KangchengLiu/RM3D
공식 코드A Data-efficient Framework for Robotics Large-scale LiDAR Scene Parsing
https://github.com/KarlXing/LUSR
공식 코드Domain Adaptation In Reinforcement Learning Via Latent Unified State Representation
https://github.com/Katexiang/EAFNet
공식 코드Polarization-driven Semantic Segmentation via Efficient Attention-bridged Fusion
https://github.com/Katexiang/ERF-PSPNET
공식 코드https://github.com/Katexiang/swiftnet
공식 코드A Comparative Study of High-Recall Real-Time Semantic Segmentation Based on Swift Factorized Network
https://github.com/KenYu910645/perspective-aware-convolution
공식 코드Perspective-aware Convolution for Monocular 3D Object Detection
https://github.com/Kguo-cs/iPad
공식 코드iPad: Iterative Proposal-centric End-to-End Autonomous Driving
https://github.com/Khrylx/AgentFormer
공식 코드AgentFormer: Agent-Aware Transformers for Socio-Temporal Multi-Agent Forecasting
https://github.com/Kin-Zhang/mmfn
공식 코드https://github.com/Kthyeon/ssfod
공식 코드Navigating Data Heterogeneity in Federated Learning A Semi-Supervised Federated Object Detection
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