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 3326–3350 of 6092 papers

TitleStatusHype
On the Adversarial Robustness of Camera-based 3D Object DetectionCode1
Autonomous particles—0
Using a Waffle Iron for Automotive Point Cloud Semantic SegmentationCode1
RangeViT: Towards Vision Transformers for 3D Semantic Segmentation in Autonomous DrivingCode1
On Multi-Agent Deep Deterministic Policy Gradients and their Explainability for SMARTS Environment—0
MAVERIC: A Data-Driven Approach to Personalized Autonomous Driving—0
FlatFormer: Flattened Window Attention for Efficient Point Cloud Transformer—0
A Light-Weight Communication-Efficient Data Sharing Approach in 5G NR V2X—0
Fast-BEV: Towards Real-time On-vehicle Bird's-Eye View PerceptionCode2
Human-Machine Collaboration for Smart Decision Making: Current Trends and Future Opportunities—0
SensorX2car: Sensors-to-car calibration for autonomous driving in road scenariosCode1
PTA-Det: Point Transformer Associating Point cloud and Image for 3D Object Detection—0
The #DNN-Verification Problem: Counting Unsafe Inputs for Deep Neural Networks—0
DR-WLC: Dimensionality Reduction cognition for object detection and pose estimation by Watching, Learning and CheckingCode0
Collaborative Perception in Autonomous Driving: Methods, Datasets and ChallengesCode1
DarkVision: A Benchmark for Low-light Image/Video Perception—0
Deep-learning-based on-chip rapid spectral imaging with high spatial resolution—0
Salient Sign Detection In Safe Autonomous Driving: AI Which Reasons Over Full Visual Context—0
Self-Supervised Image-to-Point Distillation via Semantically Tolerant Contrastive Loss—0
Time of Arrival Error Estimation for Positioning Using Convolutional Neural Networks—0
Failure Detection for Motion Prediction of Autonomous Driving: An Uncertainty Perspective—0
How Does Traffic Environment Quantitatively Affect the Autonomous Driving Prediction?—0
Optical Flow for Autonomous Driving: Applications, Challenges and Improvements—0
LENet: Lightweight And Efficient LiDAR Semantic Segmentation Using Multi-Scale Convolution AttentionCode1
Uncertainty Estimation based on Geometric Separation—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