https://github.com/Kguo-cs/iPad
공식 코드iPad: Iterative Proposal-centric End-to-End Autonomous Driving
Papers with Code 아카이브
Bench2Drive
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Bench2Drive is an autonomous driving benchmark based on the CARLA leaderboard 2.0. It consists of 220 short routes featuring safety critical scenarios. The evaluation is performed closed-loop in the CARLA simulator. The performance of an entire driving stack is being evaluated.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/OpenPerceptionX/TCP
공식 코드Trajectory-guided Control Prediction for End-to-end Autonomous Driving: A Simple yet Strong Baseline
https://github.com/Thinklab-SJTU/Bench2Drive
공식 코드Bench2Drive: Towards Multi-Ability Benchmarking of Closed-Loop End-To-End Autonomous Driving
https://github.com/autonomousvision/carla_garage
공식 코드https://github.com/hustvl/vad
공식 코드VAD: Vectorized Scene Representation for Efficient Autonomous Driving
https://github.com/liuxueyi/reasonplan
공식 코드ReasonPlan: Unified Scene Prediction and Decision Reasoning for Closed-loop Autonomous Driving
https://github.com/liyingyanucas/wote
공식 코드End-to-End Driving with Online Trajectory Evaluation via BEV World Model
https://github.com/nullmax-vision/hip-ad
공식 코드https://github.com/opendrivelab/driveadapter
공식 코드https://github.com/opendrivelab/thinktwice
공식 코드Think Twice before Driving: Towards Scalable Decoders for End-to-End Autonomous Driving
https://github.com/opendrivelab/uniad
공식 코드https://github.com/suhaisheng/difsd
공식 코드https://github.com/swc-17/sparsedrive
공식 코드SparseDrive: End-to-End Autonomous Driving via Sparse Scene Representation
https://github.com/thinklab-sjtu/bench2drivezoo
공식 코드Bench2Drive: Towards Multi-Ability Benchmarking of Closed-Loop End-To-End Autonomous Driving
https://github.com/thinklab-sjtu/drivetransformer
공식 코드DriveTransformer: Unified Transformer for Scalable End-to-End Autonomous Driving
https://github.com/woxihuanjiangguo/hydra-next
공식 코드Hydra-NeXt: Robust Closed-Loop Driving with Open-Loop Training
https://github.com/wzzheng/genad
공식 코드https://github.com/RenzKa/simlingo
Bench2Drive: Towards Multi-Ability Benchmarking of Closed-Loop End-To-End Autonomous Driving
https://github.com/linxuewu/sparse4d
SparseDrive: End-to-End Autonomous Driving via Sparse Scene Representation
https://github.com/yangyucheng000/papercode-2/tree/main/WS-VAD-mindspore-main
VAD: Vectorized Scene Representation for Efficient Autonomous Driving
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.