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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1001–1025 of 2605 papers

TitleStatusHype
Advancing Autonomous Vehicle Intelligence: Deep Learning and Multimodal LLM for Traffic Sign Recognition and Robust Lane Detection—0
Finetuning Pre-trained Model with Limited Data for LiDAR-based 3D Object Detection by Bridging Domain Gaps—0
DynaMIX: Resource Optimization for DNN-Based Real-Time Applications on a Multi-Tasking System—0
SL1-Simplex: Safe Velocity Regulation of Self-Driving Vehicles in Dynamic and Unforeseen Environments—0
Finite-Time Stabilization of Longitudinal Control for Autonomous Vehicles via a Model-Free Approach—0
Dynamics-Aware Spatiotemporal Occupancy Prediction in Urban Environments—0
First qualitative observations on deep learning vision model YOLO and DETR for automated driving in Austria—0
Bi-directional Loop Closure for Visual SLAM—0
Dynamic Prioritization of Emergency Vehicles For Self-Organizing Traffic using VTL+EV *—0
Flexible MPC-based Conflict Resolution Using Online Adaptive ADMM—0
Dynamic High-Order Control Barrier Functions with Diffuser for Safety-Critical Trajectory Planning at Signal-Free Intersections—0
BIDA: A Bi-level Interaction Decision-making Algorithm for Autonomous Vehicles in Dynamic Traffic Scenarios—0
A new platooning model for connected and autonomous vehicles to improve string stability—0
Dynamic Graph Configuration with Reinforcement Learning for Connected Autonomous Vehicle Trajectories—0
FLShield: A Validation Based Federated Learning Framework to Defend Against Poisoning Attacks—0
Fluid Batching: Exit-Aware Preemptive Serving of Early-Exit Neural Networks on Edge NPUs—0
FluidML: Fast and Memory Efficient Inference Optimization—0
FMM-X3D: FPGA-based modeling and mapping of X3D for Human Action Recognition—0
Dynamic Edge Weights in Graph Neural Networks for 3D Object Detection—0
Beyond RMSE: Do machine-learned models of road user interaction produce human-like behavior?—0
Dynamic and Static Object Detection Considering Fusion Regions and Point-wise Features—0
Dynamically Modulating Visual Place Recognition Sequence Length For Minimum Acceptable Performance Scenarios—0
Beyond One Model Fits All: Ensemble Deep Learning for Autonomous Vehicles—0
A New Multi-vehicle Trajectory Generator to Simulate Vehicle-to-Vehicle Encounters—0
Advancements in Road Lane Mapping: Comparative Fine-Tuning Analysis of Deep Learning-based Semantic Segmentation Methods Using Aerial Imagery—0
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Benchmark Results

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