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

Showing 48414850 of 6092 papers

TitleStatusHype
Learning 2D to 3D Lifting for Object Detection in 3D for Autonomous Vehicles0
Physics-Inspired Interpretability Of Machine Learning Models0
PhysNav-DG: A Novel Adaptive Framework for Robust VLM-Sensor Fusion in Navigation Applications0
SPADE: Sparse Pillar-based 3D Object Detection Accelerator for Autonomous Driving0
Information Entropy Guided Height-aware Histogram for Quantization-friendly Pillar Feature Encoder0
PillarHist: A Quantization-aware Pillar Feature Encoder based on Height-aware Histogram0
*: Improving the 3D detector by introducing Voxel2Pillar feature encoding and extracting multi-scale features0
PILOT: Efficient Planning by Imitation Learning and Optimisation for Safe Autonomous Driving0
Pilot-guided Multimodal Semantic Communication for Audio-Visual Event Localization0
PiShield: A PyTorch Package for Learning with Requirements0
Show:102550
← PrevPage 485 of 610Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ReasonNetDriving Score79.95Unverified
2InterFuserDriving Score76.18Unverified
3TCPDriving Score75.14Unverified
4TF++ WPDriving Score66.32Unverified
5Learning From All Vehicles (LAV)Driving Score61.85Unverified
6TransFuserDriving Score61.18Unverified
7TransFuser (Reproduced)Driving Score55.04Unverified
8TCP (Reproduced)Driving Score47.91Unverified
9Latent TransFuserDriving Score45.2Unverified
10GRIADDriving Score36.79Unverified
#ModelMetricClaimedVerifiedStatus
1Geometric FusionRC69.17Unverified
2TransFuserRC56.36Unverified
#ModelMetricClaimedVerifiedStatus
1Geometric FusionRC86.91Unverified
2TransFuserRC78.41Unverified