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

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Showing 381–390 of 2605 papers

TitleStatusHype
Explainable Object-induced Action Decision for Autonomous VehiclesCode1
Ford Multi-AV Seasonal DatasetCode1
Collaborative Motion Prediction via Neural Motion Message PassingCode1
BirdNet+: End-to-End 3D Object Detection in LiDAR Bird's Eye ViewCode1
MVP: Unified Motion and Visual Self-Supervised Learning for Large-Scale Robotic NavigationCode1
Spatiotemporal Learning of Multivehicle Interaction Patterns in Lane-Change ScenariosCode1
Social-STGCNN: A Social Spatio-Temporal Graph Convolutional Neural Network for Human Trajectory PredictionCode1
3D-MiniNet: Learning a 2D Representation from Point Clouds for Fast and Efficient 3D LIDAR Semantic SegmentationCode1
Real-time Fusion Network for RGB-D Semantic Segmentation Incorporating Unexpected Obstacle Detection for Road-driving ImagesCode1
Spatiotemporal Relationship Reasoning for Pedestrian Intent PredictionCode1
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Benchmark Results

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