SOTAVerified

Autonomous Driving

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.

(Image credit: Exploring the Limitations of Behavior Cloning for Autonomous Driving)

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 551–575 of 6092 papers

TitleStatusHype
DualAD: Dual-Layer Planning for Reasoning in Autonomous DrivingCode1
Efficient Motion Prediction: A Lightweight & Accurate Trajectory Prediction Model With Fast Training and Inference SpeedCode1
OneBEV: Using One Panoramic Image for Bird's-Eye-View Semantic MappingCode1
Accurate Automatic 3D Annotation of Traffic Lights and Signs for Autonomous DrivingCode1
HS3-Bench: A Benchmark and Strong Baseline for Hyperspectral Semantic Segmentation in Driving ScenariosCode1
Annealed Winner-Takes-All for Motion ForecastingCode1
ScaleFlow++: Robust and Accurate Estimation of 3D Motion from VideoCode1
SEAL: Towards Safe Autonomous Driving via Skill-Enabled Adversary Learning for Closed-Loop Scenario GenerationCode1
DiFSD: Ego-Centric Fully Sparse Paradigm with Uncertainty Denoising and Iterative Refinement for Efficient End-to-End Self-DrivingCode1
GenMapping: Unleashing the Potential of Inverse Perspective Mapping for Robust Online HD Map ConstructionCode1
ReGentS: Real-World Safety-Critical Driving Scenario Generation Made StableCode1
LED: Light Enhanced Depth Estimation at NightCode1
A Comprehensive Survey on Inverse Constrained Reinforcement Learning: Definitions, Progress and ChallengesCode1
3D-LMVIC: Learning-based Multi-View Image Coding with 3D Gaussian Geometric PriorsCode1
TASAR: Transfer-based Attack on Skeletal Action RecognitionCode1
Snapshot: Towards Application-centered Models for Pedestrian Trajectory Prediction in Urban Traffic EnvironmentsCode1
GET-UP: GEomeTric-aware Depth Estimation with Radar Points UPsamplingCode1
Trustworthy Human-AI Collaboration: Reinforcement Learning with Human Feedback and Physics Knowledge for Safe Autonomous DrivingCode1
PolarBEVDet: Exploring Polar Representation for Multi-View 3D Object Detection in Bird's-Eye-ViewCode1
A Comprehensive Review of 3D Object Detection in Autonomous Driving: Technological Advances and Future DirectionsCode1
T-FAKE: Synthesizing Thermal Images for Facial LandmarkingCode1
Co-Fix3D: Enhancing 3D Object Detection with Collaborative RefinementCode1
IMGCN: Interpretable Masked Graph Convolution Network for Pedestrian Trajectory PredictionCode1
Query3D: LLM-Powered Open-Vocabulary Scene Segmentation with Language Embedded 3D GaussianCode1
Vision-Language Guidance for LiDAR-based Unsupervised 3D Object DetectionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ReasonNetDriving Score79.95—Unverified
2InterFuserDriving Score76.18—Unverified
3TCPDriving Score75.14—Unverified
4TF++ WPDriving Score66.32—Unverified
5Learning From All Vehicles (LAV)Driving Score61.85—Unverified
6TransFuserDriving Score61.18—Unverified
7TransFuser (Reproduced)Driving Score55.04—Unverified
8TCP (Reproduced)Driving Score47.91—Unverified
9Latent TransFuserDriving Score45.2—Unverified
10GRIADDriving Score36.79—Unverified
#ModelMetricClaimedVerifiedStatus
1Geometric FusionRC69.17—Unverified
2TransFuserRC56.36—Unverified
#ModelMetricClaimedVerifiedStatus
1Geometric FusionRC86.91—Unverified
2TransFuserRC78.41—Unverified