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 1426–1450 of 6092 papers

TitleStatusHype
HybridOcc: NeRF Enhanced Transformer-based Multi-Camera 3D Occupancy Prediction—0
LOID: Lane Occlusion Inpainting and Detection for Enhanced Autonomous Driving Systems—0
MaskBEV: Towards A Unified Framework for BEV Detection and Map Segmentation—0
V2X-VLM: End-to-End V2X Cooperative Autonomous Driving Through Large Vision-Language Models—0
Diffusion Model for Planning: A Systematic Literature Review—0
PriorMapNet: Enhancing Online Vectorized HD Map Construction with Priors—0
A Transparency Paradox? Investigating the Impact of Explanation Specificity and Autonomous Vehicle Perceptual Inaccuracies on Passengers—0
CoSEC: A Coaxial Stereo Event Camera Dataset for Autonomous Driving—0
S-RAF: A Simulation-Based Robustness Assessment Framework for Responsible Autonomous DrivingCode0
A Survey of Trojan Attacks and Defenses to Deep Neural Networks—0
Learned Multimodal Compression for Autonomous Driving—0
A Conflicts-free, Speed-lossless KAN-based Reinforcement Learning Decision System for Interactive Driving in Roundabouts—0
Enhancing Expressway Ramp Merge Safety and Efficiency via Spatiotemporal Cooperative Control—0
Co-Fix3D: Enhancing 3D Object Detection with Collaborative RefinementCode1
LLMI3D: Empowering LLM with 3D Perception from a Single 2D Image—0
Panacea+: Panoramic and Controllable Video Generation for Autonomous DrivingCode3
IMGCN: Interpretable Masked Graph Convolution Network for Pedestrian Trajectory PredictionCode1
A lightweight YOLOv5-FFM model for occlusion pedestrian detection—0
Exploring Domain Shift on Radar-Based 3D Object Detection Amidst Diverse Environmental Conditions—0
FlatFusion: Delving into Details of Sparse Transformer-based Camera-LiDAR Fusion for Autonomous Driving—0
Toward Pedestrian Head Tracking: A Benchmark Dataset and an Information Fusion Network—0
A-BDD: Leveraging Data Augmentations for Safe Autonomous Driving in Adverse Weather and Lighting—0
What Matters in Autonomous Driving Anomaly Detection: A Weakly Supervised HorizonCode0
DeepInteraction++: Multi-Modality Interaction for Autonomous DrivingCode3
Eliminating Backdoors in Neural Code Models for Secure Code Understanding—0
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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