{"id":221595,"updated":"2025-01-19T14:05:40.061041+00:00","links":{},"created":"2025-01-19T01:21:35.537346+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00221595","sets":["6504:11035:11040"]},"path":["11040"],"owner":"44499","recid":"221595","title":["カメラポーズが未知の環境下での少ない画像からの深度画像を用いたNeRF"],"pubdate":{"attribute_name":"公開日","attribute_value":"2022-02-17"},"_buckets":{"deposit":"9a16be24-83ff-4c91-9e14-ecfb65ba6021"},"_deposit":{"id":"221595","pid":{"type":"depid","value":"221595","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"カメラポーズが未知の環境下での少ない画像からの深度画像を用いたNeRF","author_link":["580263","580265","580262","580264","580266"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"カメラポーズが未知の環境下での少ない画像からの深度画像を用いたNeRF"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"インタフェース","subitem_subject_scheme":"Other"}]},"item_type_id":"22","publish_date":"2022-02-17","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_22_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"早大"},{"subitem_text_value":"早大"},{"subitem_text_value":"早大"},{"subitem_text_value":"早大"},{"subitem_text_value":"早大"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/221595/files/IPSJ-Z84-7ZF-06.pdf","label":"IPSJ-Z84-7ZF-06.pdf"},"date":[{"dateType":"Available","dateValue":"2022-10-22"}],"format":"application/pdf","filename":"IPSJ-Z84-7ZF-06.pdf","filesize":[{"value":"1.1 MB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"1c87e815-da53-40d9-8470-6f7897e48690","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2022 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"佐藤, 和仁"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"武田, 司"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"岩瀬, 翔平"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"山口, 周悟"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"森島, 繁生"}],"nameIdentifiers":[{}]}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_5794","resourcetype":"conference paper"}]},"item_22_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00349328","subitem_source_identifier_type":"NCID"}]},"item_22_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"Neural Radiance Fields（NeRF）は優れた合成品質により、3Dシーンの再構成で大きな注目を集めている。しかし、NeRFの制約として、3Dシーン表現を学習するために多くの入力画像と正確なカメラポーズを必要とすることがある。本研究では、少ない画像かつ不完全なカメラポーズから深度画像を用いてNeRFを学習する手法を提案する。モデルによって推定された深度が正解の深度に近づくように損失を追加した。これにより、少ない画像からNeRFとカメラポーズを同時に最適化が可能となることを示す。","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"274","bibliographic_titles":[{"bibliographic_title":"第84回全国大会講演論文集"}],"bibliographicPageStart":"273","bibliographicIssueDates":{"bibliographicIssueDate":"2022-02-17","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2022"}]},"relation_version_is_last":true,"weko_creator_id":"44499"}}