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From 2D to 3D: AISG-SLA Visual Localization Challenge

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arxiv 2407.18590 v1 pith:DWL3H66D submitted 2024-07-26 cs.CV

From 2D to 3D: AISG-SLA Visual Localization Challenge

classification cs.CV
keywords cameravisualchallengedatalocalizationposeaisg-slaestimation
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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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 vlc-dataset@aisingapore.org.

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