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

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Showing 2701–2750 of 6092 papers

TitleStatusHype
Credal Bayesian Deep Learning—0
CSS-Segment: 2nd Place Report of LSVOS Challenge VOS Track—0
Improved and efficient inter-vehicle distance estimation using road gradients of both ego and target vehicles—0
HiLM-D: Towards High-Resolution Understanding in Multimodal Large Language Models for Autonomous Driving—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
Attack End-to-End Autonomous Driving through Module-Wise Noise—0
Improving Extrinsics between RADAR and LIDAR using Learning—0
DeepBillboard: Systematic Physical-World Testing of Autonomous Driving Systems—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
HighwayLLM: Decision-Making and Navigation in Highway Driving with RL-Informed Language Model—0
Highway Driving Dataset for Semantic Video Segmentation—0
Improving Online Lane Graph Extraction by Object-Lane Clustering—0
Improving Online Performance Prediction for Semantic Segmentation—0
C-SENN: Contrastive Self-Explaining Neural Network—0
Accurate Monocular Object Detection via Color-Embedded 3D Reconstruction for Autonomous Driving—0
Improving Point Cloud Semantic Segmentation by Learning 3D Object Detection—0
Improving Robustness and Uncertainty Modelling in Neural Ordinary Differential Equations—0
High-resolution tomographic reconstruction of optical absorbance through scattering media using neural fields—0
Improving Robustness of LiDAR-Camera Fusion Model against Weather Corruption from Fusion Strategy Perspective—0
High-Resolution Synthetic RGB-D Datasets for Monocular Depth Estimation—0
Improving the Transferability of 3D Point Cloud Attack via Spectral-aware Admix and Optimization Designs—0
DeepDyve: Dynamic Verification for Deep Neural Networks—0
Inconsistency-based Active Learning for LiDAR Object Detection—0
CSCNet: Contextual Semantic Consistency Network for Trajectory Prediction in Crowded Spaces—0
Incorporating dense metric depth into neural 3D representations for view synthesis and relighting—0
Incorporating Orientations into End-to-end Driving Model for Steering Control—0
Incorporating Recurrent Reinforcement Learning into Model Predictive Control for Adaptive Control in Autonomous Driving—0
Deep Evaluation Metric: Learning to Evaluate Simulated Radar Point Clouds for Virtual Testing of Autonomous Driving—0
Increasing the Robustness of Semantic Segmentation Models with Painting-by-Numbers—0
Incremental Reinforcement Learning --- a New Continuous Reinforcement Learning Frame Based on Stochastic Differential Equation methods—0
Independent Learning in Stochastic Games—0
High precision indoor positioning by means of LiDAR—0
High Precision Indoor Navigation for Autonomous Vehicles—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