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Learning Depth-Guided Convolutions for Monocular 3D Object Detection
[article]
2019
arXiv
pre-print
3D object detection from a single image without LiDAR is a challenging task due to the lack of accurate depth information. Conventional 2D convolutions are unsuitable for this task because they fail to capture local object and its scale information, which are vital for 3D object detection. To better represent 3D structure, prior arts typically transform depth maps estimated from 2D images into a pseudo-LiDAR representation, and then apply existing 3D point-cloud based object detectors. However,
arXiv:1912.04799v2
fatcat:5gx5lr6o45dkhe3scq5jgb2ypa