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
Adversary ML Resilience in Autonomous Driving Through Human Centered Perception Mechanisms—0
Copilot4D: Learning Unsupervised World Models for Autonomous Driving via Discrete Diffusion—0
Efficient Vision Transformer for Accurate Traffic Sign Detection—0
CenterRadarNet: Joint 3D Object Detection and Tracking Framework using 4D FMCW Radar—0
Conformal Policy Learning for Sensorimotor Control Under Distribution Shifts—0
DRNet: A Decision-Making Method for Autonomous Lane Changingwith Deep Reinforcement Learning—0
CML-MOTS: Collaborative Multi-task Learning for Multi-Object Tracking and Segmentation—0
Revealing CNN Architectures via Side-Channel Analysis in Dataflow-based Inference Accelerators—0
Enhancing the Spatial Awareness Capability of Multi-Modal Large Language Model—0
Addressing Limitations of State-Aware Imitation Learning for Autonomous Driving—0
FLODCAST: Flow and Depth Forecasting via Multimodal Recurrent Architectures—0
Safety-aware Causal Representation for Trustworthy Offline Reinforcement Learning in Autonomous Driving—0
ODM3D: Alleviating Foreground Sparsity for Semi-Supervised Monocular 3D Object DetectionCode0
Fine-Tuning Language Models Using Formal Methods Feedback—0
Guided Data Augmentation for Offline Reinforcement Learning and Imitation Learning—0
Siamese-DETR for Generic Multi-Object TrackingCode0
EqDrive: Efficient Equivariant Motion Forecasting with Multi-Modality for Autonomous Driving—0
Drive Anywhere: Generalizable End-to-end Autonomous Driving with Multi-modal Foundation Models—0
A Hybrid Graph Network for Complex Activity Detection in Video—0
YOLO-BEV: Generating Bird's-Eye View in the Same Way as 2D Object Detection—0
Driving through the Concept Gridlock: Unraveling Explainability Bottlenecks in Automated DrivingCode0
MVFAN: Multi-View Feature Assisted Network for 4D Radar Object Detection—0
ParisLuco3D: A high-quality target dataset for domain generalization of LiDAR perception—0
Using Knowledge Awareness to improve Safety of Autonomous Driving—0
Pixel-Level Clustering Network for Unsupervised Image Segmentation—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