6 accepted papers
We introduce DriveAgent, a modular multi-agent autonomous driving framework that leverages large language model (LLM) reasoning combined with multimodal sensor fusion for autonomous driving. DriveAgent orchestrates specialized agents operating on camera, Light Detection and Ranging (LiDAR), Inertial…
Feature matching is a critical task in geometric perception, yet existing methods often struggle under domain shifts and illumination changes due to reliance on visual-only learning and expensive 3D supervision. In this paper, we present TextFM, the first language-guided feature matching framework t
We introduce DriveAgent, a modular multi-agent autonomous driving framework that leverages large language model (LLM) reasoning combined with multimodal sensor fusion for autonomous driving. DriveAgent orchestrates specialized agents operating on camera, Light Detection and Ranging (LiDAR), Inertial
Concrete infrastructure often develops a variety of internal flaws that cannot be detected through visual inspection alone, and must be regularly inspected with other methods to maintain structural integrity. It has been demonstrated through previous studies that relying solely on a single non-destr
Ground Penetrating Radar (GPR) is one of the most important non-destructive evaluation (NDE) instruments to detect and locate underground objects (i.e. rebars, utility pipes). Many of the previous researches focus on GPR image-based feature detection only, and none can process sparse GPR measurement…
Ground Penetrating Radar (GPR) is one of the most important non-destructive evaluation (NDE) devices to detect the subsurface objects (i.e. rebars, utility pipes) and reveal the underground scene. One of the biggest challenges in GPR based inspection is the subsurface targets reconstruction. In orde…