PAVE: An End-to-End Dataset for Production Autonomous Vehicle Evaluation

HisTrackMap introduces a novel end-to-end tracking framework for global high-definition map construction, addressing the challenges of maintaining consistent temporal perception outcomes in autonomous driving systems. This framework utilizes historical trajectories of map elements to enhance the stability and reliability of map data collection.

MobiDiary has been introduced as a framework for Human Activity Recognition (HAR) that generates natural language descriptions of daily activities using heterogeneous physical signals, specifically IMU and Wi-Fi data. This approach addresses privacy concerns and environmental limitations associated with traditional vision-based systems.

A new paper introduces a hybrid method for Bayesian Multiobject Tracking (MOT) that integrates neural networks to enhance traditional statistical models, addressing limitations in existing approaches. This development aims to improve performance in various applications, including autonomous driving and aerospace surveillance.