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 1651–1675 of 6092 papers

TitleStatusHype
Semi-Supervised Domain Adaptation Using Target-Oriented Domain Augmentation for 3D Object DetectionCode0
A First Physical-World Trajectory Prediction Attack via LiDAR-induced Deceptions in Autonomous Driving—0
Constrained Reinforcement Learning with Average Reward Objective: Model-Based and Model-Free Algorithms—0
SparseDet: A Simple and Effective Framework for Fully Sparse LiDAR-based 3D Object Detection—0
Semantic Communication for Edge Intelligence Enabled Autonomous Driving System—0
Planning with Adaptive World Models for Autonomous Driving—0
Object Detection using Oriented Window Learning Vi-sion Transformer: Roadway Assets Recognition—0
MMVR: Millimeter-wave Multi-View Radar Dataset and Benchmark for Indoor PerceptionCode0
GenMM: Geometrically and Temporally Consistent Multimodal Data Generation for Video and LiDAR—0
Generating and Evolving Reward Functions for Highway Driving with Large Language Models—0
SparseRadNet: Sparse Perception Neural Network on Subsampled Radar Data—0
Galibr: Targetless LiDAR-Camera Extrinsic Calibration Method via Ground Plane Initialization—0
MapVision: CVPR 2024 Autonomous Grand Challenge Mapless Driving Tech Report—0
CarLLaVA: Vision language models for camera-only closed-loop drivingCode3
SemanticSpray++: A Multimodal Dataset for Autonomous Driving in Wet Surface ConditionsCode1
Research on Edge Detection of LiDAR Images Based on Artificial Intelligence Technology—0
A Two-Stage Masked Autoencoder Based Network for Indoor Depth CompletionCode1
DurLAR: A High-fidelity 128-channel LiDAR Dataset with Panoramic Ambient and Reflectivity Imagery for Multi-modal Autonomous Driving ApplicationsCode2
Cross-Modality Program Representation Learning for Electronic Design Automation with High-Level Synthesis—0
CIMRL: Combining IMitation and Reinforcement Learning for Safe Autonomous Driving—0
SimGen: Simulator-conditioned Driving Scene Generation—0
BEVSpread: Spread Voxel Pooling for Bird's-Eye-View Representation in Vision-based Roadside 3D Object DetectionCode2
Optimizing Visual Question Answering Models for Driving: Bridging the Gap Between Human and Machine Attention Patterns—0
3D-AVS: LiDAR-based 3D Auto-Vocabulary SegmentationCode1
Enhancing End-to-End Autonomous Driving with Latent World ModelCode3
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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