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 5751–5775 of 6092 papers

TitleStatusHype
Improved and efficient inter-vehicle distance estimation using road gradients of both ego and target vehicles—0
Improved Pillar with Fine-grained Feature for 3D Object Detection—0
Improved Real-Time Monocular SLAM Using Semantic Segmentation on Selective Frames—0
Improved Reinforcement Learning through Imitation Learning Pretraining Towards Image-based Autonomous Driving—0
Improved Robustness and Safety for Autonomous Vehicle Control with Adversarial Reinforcement Learning—0
Improved Single Camera BEV Perception Using Multi-Camera Training—0
Improve Uncertainty Estimation for Unknown Classes in Bayesian Neural Networks with Semi-Supervised /One Set Classification—0
Improving 3D Object Detection for Pedestrians with Virtual Multi-View Synthesis Orientation Estimation—0
Improving 3D Occupancy Prediction through Class-balancing Loss and Multi-scale Representation—0
Improving Agent Behaviors with RL Fine-tuning for Autonomous Driving—0
Improving Anomaly Segmentation with Multi-Granularity Cross-Domain Alignment—0
Improving Batch Normalization with TTA for Robust Object Detection in Self-Driving—0
Improving Bird's Eye View Semantic Segmentation by Task Decomposition—0
Diverse Multiple Trajectory Prediction Using a Two-stage Prediction Network Trained with Lane Loss—0
Improving Efficiency of DNN-based Relocalization Module for Autonomous Driving with Server-side Computing—0
Improving Extrinsics between RADAR and LIDAR using Learning—0
Improving Generalization of Reinforcement Learning with Minimax Distributional Soft Actor-Critic—0
Improving Generalization of Transfer Learning Across Domains Using Spatio-Temporal Features in Autonomous Driving—0
Improving Hierarchical Adversarial Robustness of Deep Neural Networks—0
Improving Human-AI Coordination through Online Adversarial Training and Generative Models—0
Improving Lidar-Based Semantic Segmentation of Top-View Grid Maps by Learning Features in Complementary Representations—0
Improving Motion Forecasting for Autonomous Driving with the Cycle Consistency Loss—0
Improving Online Lane Graph Extraction by Object-Lane Clustering—0
Improving Online Performance Prediction for Semantic Segmentation—0
Improving Point Cloud Semantic Segmentation by Learning 3D Object Detection—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