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 1071–1080 of 2605 papers

TitleStatusHype
FedRSU: Federated Learning for Scene Flow Estimation on Roadside UnitsCode0
Evaluating Roadside Perception for Autonomous Vehicles: Insights from Field Testing—0
ANNA: A Deep Learning Based Dataset in Heterogeneous Traffic for Autonomous VehiclesCode0
BadODD: Bangladeshi Autonomous Driving Object Detection Dataset—0
Traffic Smoothing Controllers for Autonomous Vehicles Using Deep Reinforcement Learning and Real-World Trajectory Data—0
SSL-Interactions: Pretext Tasks for Interactive Trajectory Prediction—0
Pedestrian Detection in Low-Light Conditions: A Comprehensive Survey—0
Geo-locating Road Objects using Inverse Haversine Formula with NVIDIA Driveworks—0
Hyper-STTN: Social Group-aware Spatial-Temporal Transformer Network for Human Trajectory Prediction with Hypergraph Reasoning—0
A Survey on the Applications of Frontier AI, Foundation Models, and Large Language Models to Intelligent Transportation Systems—0
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Benchmark Results

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