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 801–810 of 2605 papers

TitleStatusHype
Dynamic Edge Weights in Graph Neural Networks for 3D Object Detection—0
Dynamic Graph Configuration with Reinforcement Learning for Connected Autonomous Vehicle Trajectories—0
Dynamic High-Order Control Barrier Functions with Diffuser for Safety-Critical Trajectory Planning at Signal-Free Intersections—0
Dynamic Prioritization of Emergency Vehicles For Self-Organizing Traffic using VTL+EV *—0
Dynamics-Aware Spatiotemporal Occupancy Prediction in Urban Environments—0
DynaMIX: Resource Optimization for DNN-Based Real-Time Applications on a Multi-Tasking System—0
Bilateral Deep Reinforcement Learning Approach for Better-than-human Car Following Model—0
Dyna-Style Learning with A Macroscopic Model for Vehicle Platooning in Mixed-Autonomy Traffic—0
DyTTP: Trajectory Prediction with Normalization-Free Transformers—0
Deep learning based infrared small object segmentation: Challenges and future directions—0
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Benchmark Results

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