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 2401–2425 of 6092 papers

TitleStatusHype
Efficient Vision Transformer for Accurate Traffic Sign Detection—0
Efficient Video Understanding via Layered Multi Frame-Rate Analysis—0
Efficient Synthesis of Compact Deep Neural Networks—0
Building Safer Autonomous Agents by Leveraging Risky Driving Behavior Knowledge—0
ViewpointDepth: A New Dataset for Monocular Depth Estimation Under Viewpoint Shifts—0
Adaptive Optimization of Autonomous Vehicle Computational Resources for Performance and Energy Improvement—0
Efficient Sampling-Based Maximum Entropy Inverse Reinforcement Learning with Application to Autonomous Driving—0
Building Blocks for Robust and Effective Semi-Supervised Real-World Object Detection—0
A New Architecture for Neural Enhanced Multiobject Tracking—0
Efficient Policy Adaptation with Contrastive Prompt Ensemble for Embodied Agents—0
Efficient Perception, Planning, and Control Algorithm for Vision-Based Automated Vehicles—0
Efficient On-Chip Implementation of 4D Radar-Based 3D Object Detection on Hailo-8L—0
A New Approach to Training Multiple Cooperative Agents for Autonomous Driving—0
Adaptive Neural Networks for Intelligent Data-Driven Development—0
Efficient Multi-task Uncertainties for Joint Semantic Segmentation and Monocular Depth Estimation—0
Efficient Model-based Multi-agent Reinforcement Learning via Optimistic Equilibrium Computation—0
Efficient Mixture-of-Expert for Video-based Driver State and Physiological Multi-task Estimation in Conditional Autonomous Driving—0
Bridging the View Disparity Between Radar and Camera Features for Multi-modal Fusion 3D Object Detection—0
An Evaluation of RGB and LiDAR Fusion for Semantic Segmentation—0
Efficiently Troubleshooting Image Segmentation Models with Human-In-The-Loop—0
Bridging the Sim2Real gap with CARE: Supervised Detection Adaptation with Conditional Alignment and Reweighting—0
Efficient LiDAR Odometry for Autonomous Driving—0
Efficient Fusion and Task Guided Embedding for End-to-end Autonomous Driving—0
Bridging the Gap between Real-world and Synthetic Images for Testing Autonomous Driving Systems—0
An Evaluation of Knowledge Graph Embeddings for Autonomous Driving Data: Experience and Practice—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