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 2201–2225 of 6092 papers

TitleStatusHype
Detector Collapse: Physical-World Backdooring Object Detection to Catastrophic Overload or Blindness in Autonomous Driving—0
Action and intention recognition of pedestrians in urban traffic—0
Generic Vehicle Tracking Framework Capable of Handling Occlusions Based on Modified Mixture Particle Filter—0
Detection of Condensed Vehicle Gas Exhaust in LiDAR Point Clouds—0
A lightweight YOLOv5-FFM model for occlusion pedestrian detection—0
Detection of Adversarial Physical Attacks in Time-Series Image Data—0
Detection Is Tracking: Point Cloud Multi-Sweep Deep Learning Models Revisited—0
ACT-Bench: Towards Action Controllable World Models for Autonomous Driving—0
Detecting the Anomalies in LiDAR Pointcloud—0
AxisPose: Model-Free Matching-Free Single-Shot 6D Object Pose Estimation via Axis Generation—0
Detecting OODs as datapoints with High Uncertainty—0
A Lightweight Multi-Attack CAN Intrusion Detection System on Hybrid FPGAs—0
Generative Model-Based Fusion for Improved Few-Shot Semantic Segmentation of Infrared Images—0
Detecting Driveable Area for Autonomous Vehicles—0
Detecting Backdoor Attacks Against Point Cloud Classifiers—0
Detecting and Identifying Optical Signal Attacks on Autonomous Driving Systems—0
Detecting and adapting to crisis pattern with context based Deep Reinforcement Learning—0
Visual Perception System for Autonomous Driving—0
A Lightweight Machine Learning Pipeline for LiDAR-simulation—0
A Versatile Multi-View Framework for LiDAR-based 3D Object Detection with Guidance from Panoptic Segmentation—0
A Light-Weight Communication-Efficient Data Sharing Approach in 5G NR V2X—0
A Cross-Scale Hierarchical Transformer with Correspondence-Augmented Attention for inferring Bird's-Eye-View Semantic Segmentation—0
3D Scene Geometry-Aware Constraint for Camera Localization with Deep Learning—0
Generative One-Shot Learning (GOL): A Semi-Parametric Approach to One-Shot Learning in Autonomous Vision—0
GENESIS-RL: GEnerating Natural Edge-cases with Systematic Integration of Safety considerations and Reinforcement Learning—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