| Presentation | 2022-12-15 Training Method for Image-based Instance Segmentation by Video-based Object-Centric Representation Learning Tomokazu Kaneko, Ryosuke Sakai, Soma Shiraishi, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Object-centric representation learning (OCRL) aims to separate and extract object-wise representations from an image. There are two types of methods: image-based and video-based. The former is applicable to a static scene/image but hardly handles complex textures, while the latter is only applicable to videos yet handles textures better using object motions to separate them. We propose a novel image-based approach capable of handling complex textures in crowded scenes as effectively as video-based methods. Our approach generates pseudo labels by a video-based model on which we train an image-based model. We show its effectiveness on instance segmentation task by experiments. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Object-Centric Representation Learning / Instance Segmantation / Unsupervised Learning |
| Paper # | PRMU2022-40 |
| Date of Issue | 2022-12-08 (PRMU) |
| Conference Information | |
| Committee | PRMU |
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| Conference Date | 2022/12/15(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Toyama International Conference Center |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | Seiichi Uchida(Kyushu Univ.) |
| Vice Chair | Takuya Funatomi(NAIST) / Mitsuru Anpai(Denso IT Lab.) |
| Secretary | Takuya Funatomi(CyberAgent) / Mitsuru Anpai(Univ. of Tokyo) |
| Assistant | Nakamasa Inoue(Tokyo Inst. of Tech.) / Yasutomo Kawanishi(Riken) |
| Paper Information | |
| Registration To | Technical Committee on Pattern Recognition and Media Understanding |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Training Method for Image-based Instance Segmentation by Video-based Object-Centric Representation Learning |
| Sub Title (in English) | |
| Keyword(1) | Object-Centric Representation Learning |
| Keyword(2) | Instance Segmantation |
| Keyword(3) | Unsupervised Learning |
| 1st Author's Name | Tomokazu Kaneko |
| 1st Author's Affiliation | NEC Corporation(NEC) |
| 2nd Author's Name | Ryosuke Sakai |
| 2nd Author's Affiliation | NEC Corporation(NEC) |
| 3rd Author's Name | Soma Shiraishi |
| 3rd Author's Affiliation | NEC Corporation(NEC) |
| Date | 2022-12-15 |
| Paper # | PRMU2022-40 |
| Volume (vol) | vol.122 |
| Number (no) | PRMU-314 |
| Page | pp.pp.43-48(PRMU), |
| #Pages | 6 |
| Date of Issue | 2022-12-08 (PRMU) |