Semi-supervised Deep Multi-view Stereo

Author:

Xu Hongbin1ORCID,Chen Weitao2ORCID,Liu Yang2ORCID,Zhou Zhipeng2ORCID,Xiao Haihong1ORCID,Sun Baigui2ORCID,Xie Xuansong2ORCID,Kang Wenxiong1ORCID

Affiliation:

1. South China University of Technology, Guangzhou, China

2. Alibaba Group, Hangzhou, China

Funder

National Natural Science Foundation of China

Publisher

ACM

Reference53 articles.

1. Philip Bachman , Ouais Alsharif , and Doina Precup . 2014. Learning with pseudo-ensembles. Advances in neural information processing systems , Vol. 27 ( 2014 ). Philip Bachman, Ouais Alsharif, and Doina Precup. 2014. Learning with pseudo-ensembles. Advances in neural information processing systems, Vol. 27 (2014).

2. David Berthelot , Nicholas Carlini , Ian Goodfellow , Nicolas Papernot , Avital Oliver , and Colin A Raffel . 2019 . Mixmatch: A holistic approach to semi-supervised learning . Advances in Neural Information Processing Systems , Vol. 32 (2019). David Berthelot, Nicholas Carlini, Ian Goodfellow, Nicolas Papernot, Avital Oliver, and Colin A Raffel. 2019. Mixmatch: A holistic approach to semi-supervised learning. Advances in Neural Information Processing Systems, Vol. 32 (2019).

3. Using Multiple Hypotheses to Improve Depth-Maps for Multi-View Stereo

4. MVSNet++: Learning Depth-Based Attention Pyramid Features for Multi-View Stereo

5. Point-Based Multi-View Stereo Network

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1. DAR-MVSNet: a novel dual attention residual network for multi-view stereo;Signal, Image and Video Processing;2024-05-31

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