Unsupervised shape discovery using synchronized spectral networks
作者:
Highlights:
• A new unsupervised shape discovery method using a novel joint foreground/background segmentation and a dense part-part correspondence between all image pairs.
• A new multiscale spectral synchronization method which jointly align the spectral representations of all input images.
• A novel unsupervised superpixel-based groupwise co-registration which converts the implicit eigenvector-eigenvector synchronization to superpixel-superpixel dense correspondences.
摘要
•A new unsupervised shape discovery method using a novel joint foreground/background segmentation and a dense part-part correspondence between all image pairs.•A new multiscale spectral synchronization method which jointly align the spectral representations of all input images.•A novel unsupervised superpixel-based groupwise co-registration which converts the implicit eigenvector-eigenvector synchronization to superpixel-superpixel dense correspondences.
论文关键词:Spectral synchronization,Joint image matching,Groupwise segmentation,Shape discovery
论文评审过程:Received 19 June 2016, Revised 13 October 2016, Accepted 26 March 2017, Available online 3 April 2017, Version of Record 10 April 2017.
论文官网地址:https://doi.org/10.1016/j.patcog.2017.03.032