| Presentation | 2017-10-12 An Effective De-noising Algorithm for Making A Large Celebrity Face Dataset with A High Purity Zheng Ge, Quan Cui, Rong Xu, Masahiro Imai, Osamu Yoshie, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | In recent years, face recognition has been greatly improved by the development of CNN such as DeepID, FaceNet, and so on. However, the performance of those trained models is not satisfactory when applied on Asian face recognition because those models are almost trained on western face datasets. In order to solve such a problem, we create a large Chinese celebrity face dataset, including 11,289 celebrities and 395,130 face images, and then we can make a fine tune on those trained models for Asian face recognition by our created Chinese celebrity dataset. In this paper, we make a scheme to collect celebrity names and images from unstructured data by internet. Then we propose an effective de-noising algorithm to improve the quality of dataset, and the purity of our data can reach 97.7% from original 65.9% after the de-noising. Meanwhile, the de-noising operation on MS-Celeb-1M has been realized for evaluating the proposed method, and the purity of the tested fine part of MS-Celeb-1M has been improved from 73.0% to 98.7%. Therefore, the experiments on our created Chinese celebrity face dataset and MS-Celeb-1M indicate that the proposed de-noising algorithm has achieved excellent performance for improving the quality of dataset. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | CNNFace datasetDenoising Algorithm |
| Paper # | PRMU2017-67 |
| Date of Issue | 2017-10-05 (PRMU) |
| Conference Information | |
| Committee | PRMU |
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| Conference Date | 2017/10/12(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | Shinichi Sato(NII) |
| Vice Chair | Hironobu Fujiyoshi(Chubu Univ.) / Yoshihisa Ijiri(Omron) |
| Secretary | Hironobu Fujiyoshi(AIST) / Yoshihisa Ijiri(NAIST) |
| Assistant | Masato Ishii(NEC) / Yusuke Sugano(Osaka Univ.) |
| Paper Information | |
| Registration To | Technical Committee on Pattern Recognition and Media Understanding |
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| Language | ENG |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | An Effective De-noising Algorithm for Making A Large Celebrity Face Dataset with A High Purity |
| Sub Title (in English) | |
| Keyword(1) | CNNFace datasetDenoising Algorithm |
| 1st Author's Name | Zheng Ge |
| 1st Author's Affiliation | Waseda University(Waseda Univ.) |
| 2nd Author's Name | Quan Cui |
| 2nd Author's Affiliation | Waseda University(Waseda Univ.) |
| 3rd Author's Name | Rong Xu |
| 3rd Author's Affiliation | Datasection(Datasection Inc.) |
| 4th Author's Name | Masahiro Imai |
| 4th Author's Affiliation | Datasection(Datasection Inc.) |
| 5th Author's Name | Osamu Yoshie |
| 5th Author's Affiliation | Waseda University(Waseda Univ.) |
| Date | 2017-10-12 |
| Paper # | PRMU2017-67 |
| Volume (vol) | vol.117 |
| Number (no) | PRMU-238 |
| Page | pp.pp.25-30(PRMU), |
| #Pages | 6 |
| Date of Issue | 2017-10-05 (PRMU) |