SOTAVerified

Autonomous Vehicles

Autonomous vehicles is the task of making a vehicle that can guide itself 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: GSNet: Joint Vehicle Pose and Shape Reconstruction with Geometrical and Scene-aware Supervision )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1751–1775 of 2605 papers

TitleStatusHype
Towards Automated Safety Coverage and Testing for Autonomous Vehicles with Reinforcement Learning—0
Towards Autonomous Driving: a Multi-Modal 360^ Perception Proposal—0
Towards Better Performance and More Explainable Uncertainty for 3D Object Detection of Autonomous Vehicles—0
Towards cyber-physical systems robust to communication delays: A differential game approach—0
Towards Efficient 3D Object Detection in Bird's-Eye-View Space for Autonomous Driving: A Convolutional-Only Approach—0
Towards Event-Triggered NMPC for Efficient 6G Communications: Experimental Results and Open Problems—0
Towards Explainable, Safe Autonomous Driving with Language Embeddings for Novelty Identification and Active Learning: Framework and Experimental Analysis with Real-World Data Sets—0
Towards Generalizable and Interpretable Motion Prediction: A Deep Variational Bayes Approach—0
Towards Identifying and closing Gaps in Assurance of autonomous Road vehicleS -- a collection of Technical Notes Part 1—0
Towards Improving Robustness Against Common Corruptions in Object Detectors Using Adversarial Contrastive Learning—0
Towards learning-based planning:The nuPlan benchmark for real-world autonomous driving—0
Towards Multimodal Understanding of Passenger-Vehicle Interactions in Autonomous Vehicles: Intent/Slot Recognition Utilizing Audio-Visual Data—0
Towards Multi-Object Detection and Tracking in Urban Scenario under Uncertainties—0
Towards provable probabilistic safety for scalable embodied AI systems—0
Towards Proving the Adversarial Robustness of Deep Neural Networks—0
Towards Responsible AI: Advances in Safety, Fairness, and Accountability of Autonomous Systems—0
Towards Robust 3D Object Recognition with Dense-to-Sparse Deep Domain Adaptation—0
Towards Robust and Secure Embodied AI: A Survey on Vulnerabilities and Attacks—0
Towards Robust Human Trajectory Prediction in Raw Videos—0
Towards robust sensing for Autonomous Vehicles: An adversarial perspective—0
Towards Safe Autonomy in Hybrid Traffic: Detecting Unpredictable Abnormal Behaviors of Human Drivers via Information Sharing—0
Towards Safe, Explainable, and Regulated Autonomous Driving—0
Towards Safe Machine Learning for CPS: Infer Uncertainty from Training Data—0
Towards Safety-Aware Computing System Design in Autonomous Vehicles—0
Towards Scalable & Efficient Interaction-Aware Planning in Autonomous Vehicles using Knowledge Distillation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1BAAMA3DP22.85—Unverified
2GSNetA3DP20.21—Unverified