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 621–630 of 2605 papers

TitleStatusHype
Cross-Model Transferability of Adversarial Patches in Real-time Segmentation for Autonomous DrivingCode0
Context Model for Pedestrian Intention Prediction using Factored Latent-Dynamic Conditional Random FieldsCode0
Expecting the Unexpected: Training Detectors for Unusual Pedestrians with Adversarial ImpostersCode0
Context-aware Multi-task Learning for Pedestrian Intent and Trajectory PredictionCode0
E-Scooter Rider Detection and Classification in Dense Urban EnvironmentsCode0
Inverse++: Vision-Centric 3D Semantic Occupancy Prediction Assisted with 3D Object DetectionCode0
Estimation of Road Boundary for Intelligent Vehicles Based on DeepLabV3+ ArchitectureCode0
EP-Diffuser: An Efficient Diffusion Model for Traffic Scene Generation and Prediction via Polynomial RepresentationsCode0
Enhancing Trust Management System for Connected Autonomous Vehicles Using Machine Learning Methods: A SurveyCode0
EpiTESTER: Testing Autonomous Vehicles with Epigenetic Algorithm and Attention MechanismCode0
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Benchmark Results

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