| Presentation | 2021-08-26 Unsupervised non-rigid alignment for multiple noisy images Takanori Asanomi, Kazuya Nishimura, Heon Song, Junya Hayashida, Hiroyuki Sekiguchi, Takayuki Yagi, Imari Sato, Ryoma Bise, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | We propose a deep non-rigid alignment network that can simultaneously perform non-rigid alignment and noise decomposition of images despite severe noise and sparse errors. To address this challenging task, we introduce a low-rank loss in deep learning under the assumption that a batch of well-aligned and well-denoised images should be linearly correlated, and thus the matrix consisting the images should be low-lank. It allows us to remove the noise and corruption from input images in a self-supervised learning manner (i.e., t does not require any supervised data). In addition, we introduce a self-attention technique in order to aggregate the information about corruption from the batch of images. To the best of our knowledge, it is first attempt to introduce a low-rank loss for unsupervised deep alignment. Experiments using toy data and real medical image data demonstrate the effectiveness of the proposed method. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Unsupervised / Deep Learning / Alignment / Sparse complement |
| Paper # | PRMU2021-7 |
| Date of Issue | 2021-08-19 (PRMU) |
| Conference Information | |
| Committee | PRMU |
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| Conference Date | 2021/8/26(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | CV/PR techniques for human-robot cooperation |
| Chair | Seiichi Uchida(Kyushu Univ.) |
| Vice Chair | Masakazu Iwamura(Osaka Pref. Univ.) / Mitsuru Anpai(Denso IT Lab.) |
| Secretary | Masakazu Iwamura(NTT) / Mitsuru Anpai(Tottori Univ.) |
| Assistant | Kouta Yamaguchi(CyberAgent) / Yusuke Matsui(Univ. of Tokyo) |
| Paper Information | |
| Registration To | Technical Committee on Pattern Recognition and Media Understanding |
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| Language | ENG-JTITLE |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Unsupervised non-rigid alignment for multiple noisy images |
| Sub Title (in English) | |
| Keyword(1) | Unsupervised |
| Keyword(2) | Deep Learning |
| Keyword(3) | Alignment |
| Keyword(4) | Sparse complement |
| 1st Author's Name | Takanori Asanomi |
| 1st Author's Affiliation | Kyushu University(Kyushu Univ.) |
| 2nd Author's Name | Kazuya Nishimura |
| 2nd Author's Affiliation | Kyushu University(Kyushu Univ.) |
| 3rd Author's Name | Heon Song |
| 3rd Author's Affiliation | Kyushu University(Kyushu Univ.) |
| 4th Author's Name | Junya Hayashida |
| 4th Author's Affiliation | Kyushu University(Kyushu Univ.) |
| 5th Author's Name | Hiroyuki Sekiguchi |
| 5th Author's Affiliation | Luxonus(Kyoto Univ.) |
| 6th Author's Name | Takayuki Yagi |
| 6th Author's Affiliation | Luxonus(Luxonus) |
| 7th Author's Name | Imari Sato |
| 7th Author's Affiliation | NII(NII) |
| 8th Author's Name | Ryoma Bise |
| 8th Author's Affiliation | Kyushu University(Kyushu Univ.) |
| Date | 2021-08-26 |
| Paper # | PRMU2021-7 |
| Volume (vol) | vol.121 |
| Number (no) | PRMU-155 |
| Page | pp.pp.1-6(PRMU), |
| #Pages | 6 |
| Date of Issue | 2021-08-19 (PRMU) |