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  1. 学術雑誌論文
  2. その他
  1. 部局別インデックス
  2. 工学部

物体の重なり情報を用いた単眼深度推定

http://hdl.handle.net/20.500.12000/46170
http://hdl.handle.net/20.500.12000/46170
f235a049-8ce9-4c39-ae8c-68411c84d3d1
名前 / ファイル ライセンス アクション
JSAI2019_4I2J204.pdf JSAI2019_4I2J204.pdf
Item type デフォルトアイテムタイプ(フル)(1)
公開日 2020-06-17
タイトル
タイトル 物体の重なり情報を用いた単眼深度推定
言語 ja
作成者 高嶺, 潮

× 高嶺, 潮

ja 高嶺, 潮

遠藤, 聡志

× 遠藤, 聡志

ja 遠藤, 聡志

Kolodziejczyk, Jakub

× Kolodziejczyk, Jakub

en Kolodziejczyk, Jakub

西銘, 大喜

× 西銘, 大喜

ja 西銘, 大喜

Takamine, Michiru

× Takamine, Michiru

en Takamine, Michiru

Endo, Satoshi

× Endo, Satoshi

en Endo, Satoshi

Nishime, Taiki

× Nishime, Taiki

en Nishime, Taiki

アクセス権
アクセス権 open access
アクセス権URI http://purl.org/coar/access_right/c_abf2
権利情報
言語 ja
権利情報 一般社団法人 人工知能学会
内容記述
内容記述タイプ Other
内容記述 Depth estimation is an important tool for machines to get spatial information. Human is realizing high-accuracy depth estimation by dividing problem area, but it is difficult for machine to calculate depth from a single RGB image. Our goal is to improve the accuracy of monocular depth estimation.From the past research, it has been found that obtaining the information stepwise in the global and local areas is effective for depth estimation.Therefore, In this research, we propose a method to utilize the anteroposterior relationship information of the object. Experimental results showed that the overlap information is useful for depth prediction.
内容記述タイプ Other
内容記述 論文
出版者
言語 ja
出版者 一般社団法人 人工知能学会
言語
言語 jpn
資源タイプ
資源タイプ conference paper
資源タイプ識別子 http://purl.org/coar/resource_type/c_5794
出版タイプ
出版タイプ VoR
出版タイプResource http://purl.org/coar/version/c_970fb48d4fbd8a85
識別子
識別子 http://hdl.handle.net/20.500.12000/46170
識別子タイプ HDL
関連情報
関連識別子
識別子タイプ DOI
関連識別子 https://doi.org/10.11517/pjsai.JSAI2019.0_4I2J204
関連識別子
識別子タイプ DOI
関連識別子 https://doi.org/10.11517/pjsai.JSAI2019.0_4I2J204
収録物名
言語 ja
収録物名 人工知能学会全国大会論文集
書誌情報
巻 33, p. 4I2-J-2-04
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