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 631640 of 2605 papers

TitleStatusHype
Context-aware Multi-task Learning for Pedestrian Intent and Trajectory PredictionCode0
Expecting the Unexpected: Training Detectors for Unusual Pedestrians with Adversarial ImpostersCode0
Estimation of Road Boundary for Intelligent Vehicles Based on DeepLabV3+ ArchitectureCode0
Data-Driven Falsification of Cyber-Physical SystemsCode0
E-Scooter Rider Detection and Classification in Dense Urban EnvironmentsCode0
EpiTESTER: Testing Autonomous Vehicles with Epigenetic Algorithm and Attention MechanismCode0
Agent-aware State Estimation in Autonomous VehiclesCode0
Extending Structural Causal Models for Autonomous Vehicles to Simplify Temporal System Construction & Enable Dynamic Interactions Between AgentsCode0
Enhancing Object Detection for Autonomous Driving by Optimizing Anchor Generation and Addressing Class ImbalanceCode0
Energy Consumption Analysis of pruned Semantic Segmentation Networks on an Embedded GPUCode0
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Benchmark Results

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