Research in 3D mapping is crucial for smart city applications, yet the cost of acquiring 3D data often hinders progress. Visual localization, particularly monocular camera position estimation, offers a solution by determining the camera's pose solely through visual cues. However, this task is challenging due to limited data from a single camera. To tackle these challenges, we organized the AISG-SLA Visual Localization Challenge (VLC) at IJCAI 2023 to explore how AI can accurately extract camera pose data from 2D images in 3D space. The challenge attracted over 300 participants worldwide, forming 50+ teams. Winning teams achieved high accuracy in pose estimation using images from a car-mounted camera with low frame rates. The VLC dataset is available for research purposes upon request via [email protected].

翻译：三维地图研究对智慧城市应用至关重要，然而获取三维数据的成本往往阻碍了研究进展。视觉定位，特别是单目相机位姿估计，提供了一种解决方案——仅通过视觉线索确定相机姿态。然而，由于单相机数据有限，这项任务极具挑战性。为应对这些挑战，我们在IJCAI 2023上组织了AISG-SLA视觉定位挑战赛，旨在探索人工智能如何从二维图像中准确提取三维空间内的相机位姿数据。本次挑战赛吸引了全球300多名参与者，组成了超过50支队伍。获胜团队利用车载低帧率相机拍摄的图像，在姿态估计中实现了高精度。VLC数据集可供研究使用，可通过[email protected]申请获取。