{"id":221591,"updated":"2025-01-19T14:05:45.048475+00:00","links":{},"created":"2025-01-19T01:21:35.311469+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00221591","sets":["6504:11035:11040"]},"path":["11040"],"owner":"44499","recid":"221591","title":["リアルタイムレンダリング可能なNeRFの動的シーンへの拡張"],"pubdate":{"attribute_name":"公開日","attribute_value":"2022-02-17"},"_buckets":{"deposit":"d3446eba-60d7-4435-b983-29ebc29655f4"},"_deposit":{"id":"221591","pid":{"type":"depid","value":"221591","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"リアルタイムレンダリング可能なNeRFの動的シーンへの拡張","author_link":["580248","580246","580249","580247","580250"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"リアルタイムレンダリング可能なNeRFの動的シーンへの拡張"}]},"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/221591/files/IPSJ-Z84-7ZF-02.pdf","label":"IPSJ-Z84-7ZF-02.pdf"},"date":[{"dateType":"Available","dateValue":"2022-10-22"}],"format":"application/pdf","filename":"IPSJ-Z84-7ZF-02.pdf","filesize":[{"value":"805.7 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"41ffd368-bb25-47c2-981e-84789c223251","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":"武田, 司"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"山口, 周悟"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"岩瀬, 翔平"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"佐藤, 和仁"}],"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":"NeRF:Neural Radiance Fieldsは、入力座標・視線方向を入力とし、輝度値と密度を出力するニューラルネットワークを構築することで、高品質な新規視点画像生成手法を行う手法である。しかし、基本的に対象が静的なシーンに限定されることや、レンダリング時間が長い等の制約がある。そこで我々は、静的なシーンに限定されるものの、レンダリング時間を大幅に高速化したPlenOctrees[Yu et al.2021]を動的なシーンに拡張することで、2つの制約を解消することを試みる。具体的には、（1）入力に時刻を加えたNeRFの学習を行い、（2）各時刻におけるPlenOctreeを時刻分生成する。加えて（3）レンダラーを時刻方向に拡張することで、動的なシーンにおけるNeRFのレンダリング時間の高速化を目指す。","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"266","bibliographic_titles":[{"bibliographic_title":"第84回全国大会講演論文集"}],"bibliographicPageStart":"265","bibliographicIssueDates":{"bibliographicIssueDate":"2022-02-17","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2022"}]},"relation_version_is_last":true,"weko_creator_id":"44499"}}