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 3351–3375 of 6092 papers

TitleStatusHype
Boosting Online 3D Multi-Object Tracking through Camera-Radar Cross Check—0
Boosting the Transferability of Adversarial Samples via Attention—0
BoostRad: Enhancing Object Detection by Boosting Radar Reflections—0
Bosch Deep Learning Hardware Benchmark—0
BoT-Drive: Hierarchical Behavior and Trajectory Planning for Autonomous Driving using POMDPs—0
BOTT: Box Only Transformer Tracker for 3D Object Tracking—0
Boundary-Guided Trajectory Prediction for Road Aware and Physically Feasible Autonomous Driving—0
BoundED: Neural Boundary and Edge Detection in 3D Point Clouds via Local Neighborhood Statistics—0
Bounding Boxes, Segmentations and Object Coordinates: How Important Is Recognition for 3D Scene Flow Estimation in Autonomous Driving Scenarios?—0
Box-level Segmentation Supervised Deep Neural Networks for Accurate and Real-time Multispectral Pedestrian Detection—0
Brain2Model Transfer: Training sensory and decision models with human neural activity as a teacher—0
Brain Inspired Cognitive Model with Attention for Self-Driving Cars—0
Bridging Data-Driven and Physics-Based Models: A Consensus Multi-Model Kalman Filter for Robust Vehicle State Estimation—0
Bridging the gap between Markowitz planning and deep reinforcement learning—0
Bridging the Gap Between Multi-Step and One-Shot Trajectory Prediction via Self-Supervision—0
Bridging the Gap between Real-world and Synthetic Images for Testing Autonomous Driving Systems—0
Bridging the Sim2Real gap with CARE: Supervised Detection Adaptation with Conditional Alignment and Reweighting—0
Bridging the View Disparity Between Radar and Camera Features for Multi-modal Fusion 3D Object Detection—0
Building Blocks for Robust and Effective Semi-Supervised Real-World Object Detection—0
Building Safer Autonomous Agents by Leveraging Risky Driving Behavior Knowledge—0
Burn-In Demonstrations for Multi-Modal Imitation Learning—0
Bypass Enhancement RGB Stream Model for Pedestrian Action Recognition of Autonomous Vehicles—0
C^2INet: Realizing Incremental Trajectory Prediction with Prior-Aware Continual Causal Intervention—0
CaDeT: a Causal Disentanglement Approach for Robust Trajectory Prediction in Autonomous Driving—0
CalibFormer: A Transformer-based Automatic LiDAR-Camera Calibration Network—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