Unsupervised Multi-View CNN for Salient View Selection of 3D Objects and Scenes

ECCV 2020 Ran SongWei ZhangYitian ZhaoYonghuai Liu

We present an unsupervised 3D deep learning framework based on a ubiquitously true proposition named by us view-object consistency as it states that a 3D object and its projected 2D views always belong to the same object class. To validate its effectiveness, we design a multi-view CNN instantiating it for the salient view selection of 3D objects, which quintessentially cannot be handled by supervised learning due to the difficulty of collecting sufficient and consistent training data... (read more)

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