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 3226–3250 of 6092 papers

TitleStatusHype
SSL-OTA: Unveiling Backdoor Threats in Self-Supervised Learning for Object Detection—0
LLM-Assist: Enhancing Closed-Loop Planning with Language-Based Reasoning—0
DOEPatch: Dynamically Optimized Ensemble Model for Adversarial Patches Generation—0
Fast Quantum Convolutional Neural Networks for Low-Complexity Object Detection in Autonomous Driving Applications—0
Risk-anticipatory autonomous driving strategies considering vehicles' weights, based on hierarchical deep reinforcement learning—0
LIP-Loc: LiDAR Image Pretraining for Cross-Modal Localization—0
End-To-End Planning of Autonomous Driving in Industry and Academia: 2022-2023—0
Adaptive Kalman-based hybrid car following strategy using TD3 and CACC—0
Attention-aware Social Graph Transformer Networks for Stochastic Trajectory Prediction—0
A Survey on Open-Set Image Recognition—0
Pre-trained Trojan Attacks for Visual Recognition—0
Scaling Is All You Need: Autonomous Driving with JAX-Accelerated Reinforcement Learning—0
OKGR: Occluded Keypoint Generation and Refinement for 3D Object DetectionCode0
TimePillars: Temporally-Recurrent 3D LiDAR Object Detection—0
Lift-Attend-Splat: Bird's-eye-view camera-lidar fusion using transformers—0
Explainable Multi-Camera 3D Object Detection with Transformer-Based Saliency Maps—0
Building Lane-Level Maps from Aerial ImagesCode0
Optimizing Ego Vehicle Trajectory Prediction: The Graph Enhancement Approach—0
TADAP: Trajectory-Aided Drivable area Auto-labeling with Pre-trained self-supervised features in winter driving conditions—0
AccidentGPT: Accident Analysis and Prevention from V2X Environmental Perception with Multi-modal Large Model—0
PointeNet: A Lightweight Framework for Effective and Efficient Point Cloud Analysis—0
PPEA-Depth: Progressive Parameter-Efficient Adaptation for Self-Supervised Monocular Depth Estimation—0
An empirical study of testing machine learning in the wild—0
First qualitative observations on deep learning vision model YOLO and DETR for automated driving in Austria—0
Multi-Correlation Siamese Transformer Network with Dense Connection for 3D Single Object TrackingCode0
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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