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/YinminZhang/MonoGeo

공식 코드

Learning Geometry-Guided Depth via Projective Modeling for Monocular 3D Object Detection

https://github.com/Yiru-Jiao/UnifiedConflictDetection

공식 코드

A Unified Probabilistic Approach to Traffic Conflict Detection

https://github.com/YizhouXu-THU/CLIC

공식 코드

Continual Driving Policy Optimization with Closed-Loop Individualized Curricula

https://github.com/YuePanEdward/MULLS

공식 코드

MULLS: Versatile LiDAR SLAM via Multi-metric Linear Least Square

https://github.com/YujunHuang063/3D-GP-LMVIC

공식 코드

3D-LMVIC: Learning-based Multi-View Image Coding with 3D Gaussian Geometric Priors

https://github.com/Yzichen/FlashOCC

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FlashOcc: Fast and Memory-Efficient Occupancy Prediction via Channel-to-Height Plugin

https://github.com/ZHUANGHP/Analytic-continual-learning

공식 코드

Online Analytic Exemplar-Free Continual Learning with Large Models for Imbalanced Autonomous Driving Task

https://github.com/ZRandomize/MatrixVT

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MatrixVT: Efficient Multi-Camera to BEV Transformation for 3D Perception

https://github.com/ZhouZijie77/SegLocNet

공식 코드

SegLocNet: Multimodal Localization Network for Autonomous Driving via Bird's-Eye-View Segmentation

https://github.com/Zhourobotics/Query-3DGS-LLM

공식 코드

Query3D: LLM-Powered Open-Vocabulary Scene Segmentation with Language Embedded 3D Gaussian

https://github.com/ZikangZhou/QCNet

공식 코드

QCNeXt: A Next-Generation Framework For Joint Multi-Agent Trajectory Prediction

https://github.com/ZwwWayne/mmMOT

공식 코드

Robust Multi-Modality Multi-Object Tracking

https://github.com/a-pru/emp

공식 코드

Efficient Motion Prediction: A Lightweight & Accurate Trajectory Prediction Model With Fast Training and Inference Speed

https://github.com/a1600012888/mutr3d

공식 코드

MUTR3D: A Multi-camera Tracking Framework via 3D-to-2D Queries

https://github.com/aaltovision/cl_hscnet

공식 코드

Continual Learning for Image-Based Camera Localization

https://github.com/abastola0/cpad

공식 코드

Anomaly Detection in Cooperative Vehicle Perception Systems under Imperfect Communication

https://github.com/abdo-eldesokey/nconv

공식 코드

Confidence Propagation through CNNs for Guided Sparse Depth Regression

https://github.com/abduallahmohamed/Social-STGCNN

공식 코드

Social-STGCNN: A Social Spatio-Temporal Graph Convolutional Neural Network for Human Trajectory Prediction

https://github.com/abduallahmohamed/skeleton-graph

공식 코드

Skeleton-Graph: Long-Term 3D Motion Prediction From 2D Observations Using Deep Spatio-Temporal Graph CNNs

https://github.com/adap/flower

공식 코드

FedBN: Federated Learning on Non-IID Features via Local Batch Normalization

https://github.com/adept-thu/RoboFusion

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RoboFusion: Towards Robust Multi-Modal 3D Object Detection via SAM

https://github.com/adept-thu/dual-radar

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Dual Radar: A Multi-modal Dataset with Dual 4D Radar for Autonomous Driving

https://github.com/adlab-autodrive/bevfusion

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BEVFusion: A Simple and Robust LiDAR-Camera Fusion Framework

https://github.com/adlab-autodrive/bevheight

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BEVHeight: A Robust Framework for Vision-based Roadside 3D Object Detection

https://github.com/againerju/tcg_recognition

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Traffic Control Gesture Recognition for Autonomous Vehicles

https://github.com/agao8/STEAD

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STEAD: Spatio-Temporal Efficient Anomaly Detection for Time and Compute Sensitive Applications

https://github.com/agent-sgs/pillarnet

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PillarNet: Real-Time and High-Performance Pillar-based 3D Object Detection

https://github.com/agiresearch/asb

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Agent Security Bench (ASB): Formalizing and Benchmarking Attacks and Defenses in LLM-based Agents

https://github.com/agrimgupta92/sgan

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Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks

https://github.com/aguilarjose11/pbrlneurips

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RA-PbRL: Provably Efficient Risk-Aware Preference-Based Reinforcement Learning

https://github.com/ahydchh/impromptu-vla

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Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models

https://github.com/ai-secure/safeauto

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SafeAuto: Knowledge-Enhanced Safe Autonomous Driving with Multimodal Foundation Models

https://github.com/ai4ce/occ4cast

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LiDAR-based 4D Occupancy Completion and Forecasting

https://github.com/aiasd/fused

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Detecting Multi-Sensor Fusion Errors in Advanced Driver-Assistance Systems

https://github.com/aierlab/multitask

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Gradient-Guided Parameter Mask for Multi-Scenario Image Restoration Under Adverse Weather

https://github.com/aigeeksgroup/dc-scene

공식 코드

DC-Scene: Data-Centric Learning for 3D Scene Understanding

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