UFO: Unidentified Foreground Object Detection in 3D Point Cloud

• URL: http://arxiv.org/abs/2401.03846v1
• Date: Mon, 8 Jan 2024 12:16:06 GMT
• Title: UFO: Unidentified Foreground Object Detection in 3D Point Cloud
• Authors: Hyunjun Choi, Hawook Jeong, Jin Young Choi
• Abstract summary: Existing 3D object detectors encounter hard challenges in both 3D localization and Out-of-Distribution detection. We suggest a new UFO detection framework including three tasks: evaluation protocol, methodology, and benchmark. The proposed framework consistently enhances performance by a large margin across all four baseline detectors.
• Score: 7.286344230797102
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In this paper, we raise a new issue on Unidentified Foreground Object (UFO) detection in 3D point clouds, which is a crucial technology in autonomous driving in the wild. UFO detection is challenging in that existing 3D object detectors encounter extremely hard challenges in both 3D localization and Out-of-Distribution (OOD) detection. To tackle these challenges, we suggest a new UFO detection framework including three tasks: evaluation protocol, methodology, and benchmark. The evaluation includes a new approach to measure the performance on our goal, i.e. both localization and OOD detection of UFOs. The methodology includes practical techniques to enhance the performance of our goal. The benchmark is composed of the KITTI Misc benchmark and our additional synthetic benchmark for modeling a more diverse range of UFOs. The proposed framework consistently enhances performance by a large margin across all four baseline detectors: SECOND, PointPillars, PV-RCNN, and PartA2, giving insight for future work on UFO detection in the wild.

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