May 14, 2024, 4:46 a.m. | Xueying Jiang, Sheng Jin, Xiaoqin Zhang, Ling Shao, Shijian Lu

cs.CV updates on

arXiv:2405.07696v1 Announce Type: new
Abstract: Monocular 3D object detection aims for precise 3D localization and identification of objects from a single-view image. Despite its recent progress, it often struggles while handling pervasive object occlusions that tend to complicate and degrade the prediction of object dimensions, depths, and orientations. We design MonoMAE, a monocular 3D detector inspired by Masked Autoencoders that addresses the object occlusion issue by masking and reconstructing objects in the feature space. MonoMAE consists of two novel designs. …

3d object 3d object detection abstract arxiv autoencoders design detection dimensions identification image localization object objects prediction progress through type view while

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