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 1576–1600 of 6092 papers

TitleStatusHype
C^2INet: Realizing Incremental Trajectory Prediction with Prior-Aware Continual Causal Intervention—0
An Expert Ensemble for Detecting Anomalous Scenes, Interactions, and Behaviors in Autonomous Driving—0
Dynamic Point Cloud Denoising via Manifold-to-Manifold Distance—0
DySS: Dynamic Queries and State-Space Learning for Efficient 3D Object Detection from Multi-Camera Videos—0
Bypass Enhancement RGB Stream Model for Pedestrian Action Recognition of Autonomous Vehicles—0
Burn-In Demonstrations for Multi-Modal Imitation Learning—0
Attended Temperature Scaling: A Practical Approach for Calibrating 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
Model Hijacking Attack in Federated Learning—0
DyTTP: Trajectory Prediction with Normalization-Free Transformers—0
Building Blocks for Robust and Effective Semi-Supervised Real-World Object Detection—0
A New Architecture for Neural Enhanced Multiobject Tracking—0
RGB and LiDAR fusion based 3D Semantic Segmentation for Autonomous Driving—0
A New Approach to Training Multiple Cooperative Agents for Autonomous Driving—0
Adaptive Neural Networks for Intelligent Data-Driven Development—0
DynRsl-VLM: Enhancing Autonomous Driving Perception with Dynamic Resolution Vision-Language Models—0
An Evaluation of RGB and LiDAR Fusion for Semantic Segmentation—0
Bridging the View Disparity Between Radar and Camera Features for Multi-modal Fusion 3D Object Detection—0
Adaptive Kalman-based hybrid car following strategy using TD3 and CACC—0
Bridging the Sim2Real gap with CARE: Supervised Detection Adaptation with Conditional Alignment and Reweighting—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
6DOPE-GS: Online 6D Object Pose Estimation using Gaussian Splatting—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