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/imadalishah/HSI_SemanticSegmentationModels_AD_ADAS

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Hyperspectral Imaging-Based Perception in Autonomous Driving Scenarios: Benchmarking Baseline Semantic Segmentation Models

https://github.com/imoneoi/carla_env

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A Versatile and Efficient Reinforcement Learning Framework for Autonomous Driving

https://github.com/imoneoi/onerl

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A Versatile and Efficient Reinforcement Learning Framework for Autonomous Driving

https://github.com/imran2205/logicrag

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Logic-RAG: Augmenting Large Multimodal Models with Visual-Spatial Knowledge for Road Scene Understanding

https://github.com/intelligent-control-lab/guard

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GUARD: A Safe Reinforcement Learning Benchmark

https://github.com/intelligent-control-lab/statewise_constrained_policy_optimization

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State-wise Constrained Policy Optimization

https://github.com/intelligent-vehicles/bevdriver

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BEVDriver: Leveraging BEV Maps in LLMs for Robust Closed-Loop Driving

https://github.com/internlandmark/landmarksystem

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LandMarkSystem Technical Report

https://github.com/internlm/lmdeploy

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AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration

https://github.com/intrinsic-ai/collision-avoidance-metric

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Collision Avoidance Metric for 3D Camera Evaluation

https://github.com/irohxu/awesome-multimodal-llm-autonomous-driving

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A Survey on Multimodal Large Language Models for Autonomous Driving

https://github.com/islab-github/VOBEM2

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Role of Sensing and Computer Vision in 6G Wireless Communications

https://github.com/ispc-lab/lidar4d

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LiDAR4D: Dynamic Neural Fields for Novel Space-time View LiDAR Synthesis

https://github.com/ispc-lab/marl4ad

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Multi-Agent Reinforcement Learning for Autonomous Driving: A Survey

https://github.com/ispc-lab/neuralpci

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NeuralPCI: Spatio-temporal Neural Field for 3D Point Cloud Multi-frame Non-linear Interpolation

https://github.com/iurada/neutron-segmentation

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Transient Fault Tolerant Semantic Segmentation for Autonomous Driving

https://github.com/ixilai/awfusion

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All-weather Multi-Modality Image Fusion: Unified Framework and 100k Benchmark

https://github.com/j-cap/FL-based-neural-FF-control

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Federated Learning for Privacy-Preserving Feedforward Control in Multi-Agent Systems

https://github.com/jacobieee/st-mr

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Graph-based Spatial Transformer with Memory Replay for Multi-future Pedestrian Trajectory Prediction

https://github.com/jacobwang925/path-integral-pinn

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Physics-Informed Representation and Learning: Control and Risk Quantification

https://github.com/jaewoo97/kdtf

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Multi-modal Knowledge Distillation-based Human Trajectory Forecasting

https://github.com/jameszhou-gl/gpt-4v-distribution-shift

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How Well Does GPT-4V(ision) Adapt to Distribution Shifts? A Preliminary Investigation

https://github.com/janegerken/heal-swin

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HEAL-SWIN: A Vision Transformer On The Sphere

https://github.com/janmarcelkezmann/metadetect3d

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LMD: Light-weight Prediction Quality Estimation for Object Detection in Lidar Point Clouds

https://github.com/jarvishou829/sups

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SUPS: A Simulated Underground Parking Scenario Dataset for Autonomous Driving

https://github.com/jasmine-tjy/semantic-based-point-cloud-tasks

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Implicit Guidance and Explicit Representation of Semantic Information in Points Cloud: A Survey

https://github.com/jasonkks/pttr

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Exploring Point-BEV Fusion for 3D Point Cloud Object Tracking with Transformer

https://github.com/jasonxu1225/awesome-constraint-inference-in-rl

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A Comprehensive Survey on Inverse Constrained Reinforcement Learning: Definitions, Progress and Challenges

https://github.com/javyduck/ChatScene

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ChatScene: Knowledge-Enabled Safety-Critical Scenario Generation for Autonomous Vehicles

https://github.com/jayLEE0301/vq_bet_official

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Behavior Generation with Latent Actions

https://github.com/jbji/repvf

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RepVF: A Unified Vector Fields Representation for Multi-task 3D Perception

https://github.com/jbwang1997/OPUS

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OPUS: Occupancy Prediction Using a Sparse Set

https://github.com/jchengai/forecast-mae

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Forecast-MAE: Self-supervised Pre-training for Motion Forecasting with Masked Autoencoders

https://github.com/jeffwang987/asap

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Are We Ready for Vision-Centric Driving Streaming Perception? The ASAP Benchmark

https://github.com/jeffwang987/openoccupancy

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OpenOccupancy: A Large Scale Benchmark for Surrounding Semantic Occupancy Perception

https://github.com/jeongjin0/invisible-backdoor-object-detection

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Mask-based Invisible Backdoor Attacks on Object Detection

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