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 1026–1050 of 6092 papers

TitleStatusHype
DiffusionDrive: Truncated Diffusion Model for End-to-End Autonomous DrivingCode5
Enhancing Autonomous Driving Safety through World Model-Based Predictive Navigation and Adaptive Learning Algorithms for 5G Wireless Applications—0
MSSF: A 4D Radar and Camera Fusion Framework With Multi-Stage Sampling for 3D Object Detection in Autonomous Driving—0
LiDAR-based End-to-end Temporal Perception for Vehicle-Infrastructure Cooperation—0
TopoSD: Topology-Enhanced Lane Segment Perception with SDMap Prior—0
Open Challenges in the Formal Verification of Autonomous Driving—0
Understanding World or Predicting Future? A Comprehensive Survey of World Models—0
Formal Simulation and Visualisation of Hybrid Programs—0
A Systematic Study of Multi-Agent Deep Reinforcement Learning for Safe and Robust Autonomous Highway Ramp Entry—0
Model Checking for Reinforcement Learning in Autonomous Driving: One Can Do More Than You Think!—0
MagicDriveDiT: High-Resolution Long Video Generation for Autonomous Driving with Adaptive Control—0
WARLearn: Weather-Adaptive Representation LearningCode0
FedRAV: Hierarchically Federated Region-Learning for Traffic Object Classification of Autonomous VehiclesCode0
A Survey on Adversarial Robustness of LiDAR-based Machine Learning Perception in Autonomous Vehicles—0
MambaDETR: Query-based Temporal Modeling using State Space Model for Multi-View 3D Object Detection—0
Hints of Prompt: Enhancing Visual Representation for Multimodal LLMs in Autonomous Driving—0
DriveMLLM: A Benchmark for Spatial Understanding with Multimodal Large Language Models in Autonomous DrivingCode2
WHALES: A Multi-agent Scheduling Dataset for Enhanced Cooperation in Autonomous DrivingCode1
YCB-LUMA: YCB Object Dataset with Luminance Keying for Object LocalizationCode0
LaVida Drive: Vision-Text Interaction VLM for Autonomous Driving with Token Selection, Recovery and Enhancement—0
A Resource Efficient Fusion Network for Object Detection in Bird's-Eye View using Camera and Raw Radar DataCode0
Provably Efficient Action-Manipulation Attack Against Continuous Reinforcement Learning—0
Robust 3D Semantic Occupancy Prediction with Calibration-free Spatial TransformationCode1
Motif Channel Opened in a White-Box: Stereo Matching via Motif Correlation GraphCode2
C^2INet: Realizing Incremental Trajectory Prediction with Prior-Aware Continual Causal Intervention—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