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 2051–2075 of 6092 papers

TitleStatusHype
RangeLDM: Fast Realistic LiDAR Point Cloud GenerationCode1
Real-Time Image Segmentation via Hybrid Convolutional-Transformer Architecture SearchCode1
Enhancing Human-Centered Dynamic Scene Understanding via Multiple LLMs Collaborated Reasoning—0
RCooper: A Real-world Large-scale Dataset for Roadside Cooperative PerceptionCode2
Gradient based Feature Attribution in Explainable AI: A Technical Review—0
E2E-MFD: Towards End-to-End Synchronous Multimodal Fusion DetectionCode2
On STPA for Distributed Development of Safe Autonomous Driving: An Interview Study—0
Intention-aware Denoising Diffusion Model for Trajectory Prediction—0
GenAD: Generalized Predictive Model for Autonomous DrivingCode7
PreSight: Enhancing Autonomous Vehicle Perception with City-Scale NeRF PriorsCode1
Are you a robot? Detecting Autonomous Vehicles from Behavior Analysis—0
Metasurface-Enabled Multifunctional Single-Frequency Sensors without External Power—0
FogGuard: guarding YOLO against fog using perceptual lossCode0
CLIP-BEVFormer: Enhancing Multi-View Image-Based BEV Detector with Ground Truth Flow—0
MIM4D: Masked Modeling with Multi-View Video for Autonomous Driving Representation LearningCode2
Real-time 3D semantic occupancy prediction for autonomous vehicles using memory-efficient sparse convolution—0
DeepCSHAP: Utilizing Shapley Values to Explain Deep Complex-Valued Neural Networks—0
Offboard Occupancy Refinement with Hybrid Propagation for Autonomous DrivingCode1
LIX: Implicitly Infusing Spatial Geometric Prior Knowledge into Visual Semantic Segmentation for Autonomous Driving—0
Optimized Detection and Classification on GTRSB: Advancing Traffic Sign Recognition with Convolutional Neural Networks—0
Adaptive Fusion of Single-View and Multi-View Depth for Autonomous DrivingCode2
Adaptive Bounding Box Uncertainties via Two-Step Conformal PredictionCode1
Tractable Joint Prediction and Planning over Discrete Behavior Modes for Urban Driving—0
Unleashing HyDRa: Hybrid Fusion, Depth Consistency and Radar for Unified 3D PerceptionCode1
A Survey of Vision Transformers in Autonomous Driving: Current Trends and Future Directions—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