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 1401–1425 of 2605 papers

TitleStatusHype
S2TNet: Spatio-Temporal Transformer Networks for Trajectory Prediction in Autonomous DrivingCode1
CoCoPIE XGen: A Full-Stack AI-Oriented Optimizing Framework—0
Demystifying the Adversarial Robustness of Random Transformation DefensesCode0
Holistic Transformer: A Joint Neural Network for Trajectory Prediction and Decision-Making of Autonomous Vehicles—0
A Comprehensive Eco-Driving Strategy for Connected and Autonomous Vehicles (CAVs) with Microscopic Traffic Simulation Testing Evaluation—0
Online Segmentation of LiDAR Sequences: Dataset and AlgorithmCode1
Simple-BEV: What Really Matters for Multi-Sensor BEV Perception?—0
Waymo Open Dataset: Panoramic Video Panoptic Segmentation—0
Energy Consumption Analysis of pruned Semantic Segmentation Networks on an Embedded GPUCode0
Receding Moving Object Segmentation in 3D LiDAR Data Using Sparse 4D ConvolutionsCode2
Effects of Augmented-Reality-Based Assisting Interfaces on Drivers' Object-wise Situational Awareness in Highly Autonomous Vehicles—0
Slim-neck by GSConv: A lightweight-design for real-time detector architecturesCode2
Radar Guided Dynamic Visual Attention for Resource-Efficient RGB Object Detection—0
Watch Out for the Safety-Threatening Actors: Proactively Mitigating Safety Hazards—0
A Hierarchical Pedestrian Behavior Model to Generate Realistic Human Behavior in Traffic Simulation—0
Continual Object Detection: A review of definitions, strategies, and challenges—0
Edge YOLO: Real-Time Intelligent Object Detection System Based on Edge-Cloud Cooperation in Autonomous Vehicles—0
P2M-DeTrack: Processing-in-Pixel-in-Memory for Energy-efficient and Real-Time Multi-Object Detection and Tracking—0
OpenCalib: A Multi-sensor Calibration Toolbox for Autonomous DrivingCode4
Deep Sensor Fusion with Pyramid Fusion Networks for 3D Semantic SegmentationCode1
Efficient textual explanations for complex road and traffic scenarios based on semantic segmentation—0
The risk ethics of autonomous vehicles: a continuous trolley problem in regular road traffic—0
Wireless Ad Hoc Federated Learning: A Fully Distributed Cooperative Machine Learning—0
VPAIR -- Aerial Visual Place Recognition and Localization in Large-scale Outdoor EnvironmentsCode1
E-Scooter Rider Detection and Classification in Dense Urban EnvironmentsCode0
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Benchmark Results

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