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Objectron: A Large Scale Dataset of Object-Centric Videos in the Wild with Pose Annotations

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arxiv 2012.09988 v1 pith:B6KETGAI submitted 2020-12-18 cs.CV

Objectron: A Large Scale Dataset of Object-Centric Videos in the Wild with Pose Annotations

Adel Ahmadyan , Liangkai Zhang , Jianing Wei , Artsiom Ablavatski , Matthias Grundmann This is my paper
classification cs.CV
keywords datasetobjectdetectionobjectronvideosannotatedannotationsapplications
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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3D object detection has recently become popular due to many applications in robotics, augmented reality, autonomy, and image retrieval. We introduce the Objectron dataset to advance the state of the art in 3D object detection and foster new research and applications, such as 3D object tracking, view synthesis, and improved 3D shape representation. The dataset contains object-centric short videos with pose annotations for nine categories and includes 4 million annotated images in 14,819 annotated videos. We also propose a new evaluation metric, 3D Intersection over Union, for 3D object detection. We demonstrate the usefulness of our dataset in 3D object detection tasks by providing baseline models trained on this dataset. Our dataset and evaluation source code are available online at http://www.objectron.dev

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