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 1826–1850 of 6092 papers

TitleStatusHype
Novel Actor-Critic Algorithm for Robust Decision Making of CAV under Delays and Loss of V2X Data—0
A Survey on Occupancy Perception for Autonomous Driving: The Information Fusion PerspectiveCode4
Multi-Modal Data-Efficient 3D Scene Understanding for Autonomous DrivingCode3
Tiny Deep Ensemble: Uncertainty Estimation in Edge AI Accelerators via Ensembling Normalization Layers with Shared Weights—0
Roadside Units Assisted Localized Automated Vehicle Maneuvering: An Offline Reinforcement Learning Approach—0
Unified End-to-End V2X Cooperative Autonomous Driving—0
DriveWorld: 4D Pre-trained Scene Understanding via World Models for Autonomous Driving—0
Deep Event-based Object Detection in Autonomous Driving: A Survey—0
TorchDriveEnv: A Reinforcement Learning Benchmark for Autonomous Driving with Reactive, Realistic, and Diverse Non-Playable Characters—0
ESP: Extro-Spective Prediction for Long-term Behavior Reasoning in Emergency Scenarios—0
Role of Sensing and Computer Vision in 6G Wireless CommunicationsCode0
Feature Map Convergence Evaluation for Functional Module—0
UniGen: Unified Modeling of Initial Agent States and Trajectories for Generating Autonomous Driving Scenarios—0
BadFusion: 2D-Oriented Backdoor Attacks against 3D Object Detection—0
SocialFormer: Social Interaction Modeling with Edge-enhanced Heterogeneous Graph Transformers for Trajectory Prediction—0
Is Sora a World Simulator? A Comprehensive Survey on General World Models and BeyondCode4
SalFAU-Net: Saliency Fusion Attention U-Net for Salient Object Detection—0
Vision-based 3D occupancy prediction in autonomous driving: a review and outlookCode3
Obstacle Avoidance of Autonomous Vehicles: An LPVMPC with Scheduling Trust Region—0
DiffMap: Enhancing Map Segmentation with Map Prior Using Diffusion Model—0
M^2Depth: Self-supervised Two-Frame Multi-camera Metric Depth Estimation—0
MFTraj: Map-Free, Behavior-Driven Trajectory Prediction for Autonomous Driving—0
Multi-Space Alignments Towards Universal LiDAR SegmentationCode2
OmniDrive: A Holistic Vision-Language Dataset for Autonomous Driving with Counterfactual ReasoningCode4
Federated Learning with Heterogeneous Data Handling for Robust Vehicular Object DetectionCode0
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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