Completing point cloud from few points by Wasserstein GAN and Transformers

In many vision and robotics applications, it is common that the captured objects are represented by very few points. Most of the existing completion methods are designed for partial point clouds with many points, and they perform poorly or even fail completely in the case of few points. However, due...

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Bibliographische Detailangaben

Hauptverfasser:	Wu, Xianfeng, Qian, Jinhui, Wei, Qing, Wu, Xianzu, Liu, Xinyi, Hu, Luxin, Gong, Yanli, Lai, Zhongyuan, Wu, Libing
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Computer Vision and Pattern Recognition
Online-Zugang:	Volltext bestellen
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