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

Showing 701710 of 2605 papers

TitleStatusHype
Towards learning-based planning:The nuPlan benchmark for real-world autonomous driving0
Generalizing Cooperative Eco-driving via Multi-residual Task Learning0
A Multi-Task Oriented Semantic Communication Framework for Autonomous Vehicles0
Multi-task Learning for Real-time Autonomous Driving Leveraging Task-adaptive Attention Generator0
HoloVIC: Large-scale Dataset and Benchmark for Multi-Sensor Holographic Intersection and Vehicle-Infrastructure Cooperative0
Improved LiDAR Odometry and Mapping using Deep Semantic Segmentation and Novel Outliers Detection0
Cooperative and Interaction-aware Driver Model for Lane Change Maneuver0
COMMIT: Certifying Robustness of Multi-Sensor Fusion Systems against Semantic Attacks0
OccFusion: Multi-Sensor Fusion Framework for 3D Semantic Occupancy PredictionCode2
Region-Transformer: Self-Attention Region Based Class-Agnostic Point Cloud Segmentation0
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Benchmark Results

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