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Jan, 2024
面向基于视觉的道路边缘三维物体检测的场景泛化
Towards Scenario Generalization for Vision-based Roadside 3D Object Detection
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Lei Yang, Xinyu Zhang, Jun Li, Li Wang, Chuang Zhang...
TL;DR
该研究论文提出了一种名为SGV3D的创新道路边缘3D物体检测方案,通过背景抑制模块(BSM)减少视觉中心流程中的背景过拟合问题,并利用半监督数据生成流程(SSDG)利用新场景中的未标记图像生成具有不同摄像机姿态的多样化实例前景,从而提高了在新场景中的检测准确性。
Abstract
roadside perception
can greatly increase the safety of
autonomous vehicles
by extending their perception ability beyond the visual range and addressing blind spots. However, current state-of-the-art vision-based
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