Papers with Code 아카이브

Autonomous Driving

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

하위 태스크: 6
평가표: 4
보존된 평가 기록: 23

Autonomous driving is the task of driving a vehicle 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: 0.5">(Image credit: Exploring the Limitations of Behavior Cloning for Autonomous Driving)</span>

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/zhanghm1995/forge_vfm4ad

공식 코드

Forging Vision Foundation Models for Autonomous Driving: Challenges, Methodologies, and Opportunities

https://github.com/zhangsn-19/pan

공식 코드

Towards Benchmarking and Assessing Visual Naturalness of Physical World Adversarial Attacks

https://github.com/zhangyong-tang/gmmt

공식 코드

Awesome Multi-modal Object Tracking

https://github.com/zhangyp15/beverse

공식 코드

BEVerse: Unified Perception and Prediction in Birds-Eye-View for Vision-Centric Autonomous Driving

https://github.com/zhangyp15/graphad

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GraphAD: Interaction Scene Graph for End-to-end Autonomous Driving

https://github.com/zhangyp15/occformer

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OccFormer: Dual-path Transformer for Vision-based 3D Semantic Occupancy Prediction

https://github.com/zhangyp15/simmod

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A Simple Baseline for Multi-Camera 3D Object Detection

https://github.com/zhanwei-z/g2ltraj

공식 코드

G2LTraj: A Global-to-Local Generation Approach for Trajectory Prediction

https://github.com/zhefan-xu/cerlab-uav-autonomy

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A real-time dynamic obstacle tracking and mapping system for UAV navigation and collision avoidance with an RGB-D camera

https://github.com/zhejz/carla-roach

공식 코드

End-to-End Urban Driving by Imitating a Reinforcement Learning Coach

https://github.com/zhejz/hptr

공식 코드

Real-Time Motion Prediction via Heterogeneous Polyline Transformer with Relative Pose Encoding

https://github.com/zhejz/trafficbots

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TrafficBots: Towards World Models for Autonomous Driving Simulation and Motion Prediction

https://github.com/zhenzhenxiang/SemanticsSharing

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Boosting Real-Time Driving Scene Parsing with Shared Semantics

https://github.com/zhijian11/DriveMM

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DriveMM: All-in-One Large Multimodal Model for Autonomous Driving

https://github.com/zhiqi-li/BEVFormer

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BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformers

https://github.com/zhiqic/DAMO-StreamNet

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DAMO-StreamNet: Optimizing Streaming Perception in Autonomous Driving

https://github.com/zhiqic/longshortnet

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LongShortNet: Exploring Temporal and Semantic Features Fusion in Streaming Perception

https://github.com/zhiyuanli218/segret

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SegRet: An Efficient Design for Semantic Segmentation with Retentive Network

https://github.com/zhonghuayi/focusflow_official

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FocusFlow: Boosting Key-Points Optical Flow Estimation for Autonomous Driving

https://github.com/zhonghuayi/optical_flow_robustness_benchmark

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Benchmarking the Robustness of Optical Flow Estimation to Corruptions

https://github.com/zhouqiu/sogdet

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SOGDet: Semantic-Occupancy Guided Multi-view 3D Object Detection

https://github.com/zhourobotics/reasondrive

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ReasonDrive: Efficient Visual Question Answering for Autonomous Vehicles with Reasoning-Enhanced Small Vision-Language Models

https://github.com/zhouzheyuan/sgm3d

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SGM3D: Stereo Guided Monocular 3D Object Detection

https://github.com/zhujunli1993/swindepose

공식 코드

Depth-based 6DoF Object Pose Estimation using Swin Transformer

https://github.com/zhumorui/m3cad

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M3CAD: Towards Generic Cooperative Autonomous Driving Benchmark

https://github.com/zhuoinoulu/svnet

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SVNet: Where SO(3) Equivariance Meets Binarization on Point Cloud Representation

https://github.com/zhuxing0/sa-radar

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Simulate Any Radar: Attribute-Controllable Radar Simulation via Waveform Parameter Embedding

https://github.com/zilin-huang/HAIM-DRL

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HAIM-DRL: Enhanced Human-in-the-loop Reinforcement Learning for Safe and Efficient Autonomous Driving

https://github.com/zilin-huang/PE-RLHF

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Trustworthy Human-AI Collaboration: Reinforcement Learning with Human Feedback and Physics Knowledge for Safe Autonomous Driving

https://github.com/ziongo6/fadet

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FADet: A Multi-sensor 3D Object Detection Network based on Local Featured Attention

https://github.com/ziongo6/hawkdrive

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HawkDrive: A Transformer-driven Visual Perception System for Autonomous Driving in Night Scene

https://github.com/zippiest/yolo-cca

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YOLO-CCA: A Context-Based Approach for Traffic Sign Detection

https://github.com/ziqipang/lm4visualencoding

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Frozen Transformers in Language Models Are Effective Visual Encoder Layers

https://github.com/ziqipang/streamingforecasting

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Streaming Motion Forecasting for Autonomous Driving

https://github.com/ziquanliu/ICML2024-AT-UR

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The Pitfalls and Promise of Conformal Inference Under Adversarial Attacks

https://github.com/zirui0625/difiisr

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DifIISR: A Diffusion Model with Gradient Guidance for Infrared Image Super-Resolution

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.