PUFA-GAN: A Frequency-Aware Generative Adversarial Network for 3D Point Cloud Upsampling

We propose a generative adversarial network for point cloud upsampling, which can not only make the upsampled points evenly distributed on the underlying surface but also efficiently generate clean high frequency regions. The generator of our network includes a dynamic graph hierarchical residual ag...

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Veröffentlicht in:	IEEE transactions on image processing 2022, Vol.31, p.1-1
Hauptverfasser:	Liu, Hao, Yuan, Hui, Hou, Junhui, Hamzaoui, Raouf, Gao, Wei
Format:	Artikel
Sprache:	eng
Schlagworte:	Agglomeration deep learning Discriminators Feature extraction Generative adversarial networks graph filter Graph theory High frequencies Point cloud upsampling Three dimensional models
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