{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,27]],"date-time":"2025-07-27T07:33:45Z","timestamp":1753601625548,"version":"3.37.3"},"reference-count":40,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"10","license":[{"start":{"date-parts":[[2024,10,1]],"date-time":"2024-10-01T00:00:00Z","timestamp":1727740800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,10,1]],"date-time":"2024-10-01T00:00:00Z","timestamp":1727740800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,10,1]],"date-time":"2024-10-01T00:00:00Z","timestamp":1727740800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"National Key Research and Development Program of China","award":["2022YFB3305004"],"award-info":[{"award-number":["2022YFB3305004"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Robot. Autom. Lett."],"published-print":{"date-parts":[[2024,10]]},"DOI":"10.1109\/lra.2024.3444671","type":"journal-article","created":{"date-parts":[[2024,8,15]],"date-time":"2024-08-15T17:47:25Z","timestamp":1723744045000},"page":"8306-8313","source":"Crossref","is-referenced-by-count":1,"title":["AMVP: Adaptive Multi-Volume Primitives for Auto-Driving Novel View Synthesis"],"prefix":"10.1109","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5996-382X","authenticated-orcid":false,"given":"Dexin","family":"Qi","sequence":"first","affiliation":[{"name":"School of Mechanical Engineering and the Shaanxi Key Laboratory of Intelligent Robots, Xi&#x0027;an Jiaotong University, Xi&#x0027;an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7333-7953","authenticated-orcid":false,"given":"Tao","family":"Tao","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering and the Shaanxi Key Laboratory of Intelligent Robots, Xi&#x0027;an Jiaotong University, Xi&#x0027;an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-5882-9806","authenticated-orcid":false,"given":"Zhihong","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering and the Shaanxi Key Laboratory of Intelligent Robots, Xi&#x0027;an Jiaotong University, Xi&#x0027;an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6505-2774","authenticated-orcid":false,"given":"Xuesong","family":"Mei","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering and the Shaanxi Key Laboratory of Intelligent Robots, Xi&#x0027;an Jiaotong University, Xi&#x0027;an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"doi-asserted-by":"publisher","key":"ref1","DOI":"10.1126\/scirobotics.aaw0863"},{"doi-asserted-by":"publisher","key":"ref2","DOI":"10.1109\/CVPR46437.2021.00715"},{"doi-asserted-by":"publisher","key":"ref3","DOI":"10.1109\/CVPR52729.2023.00140"},{"doi-asserted-by":"publisher","key":"ref4","DOI":"10.1007\/978-3-030-58452-8_24"},{"doi-asserted-by":"publisher","key":"ref5","DOI":"10.1109\/CVPR52729.2023.00404"},{"doi-asserted-by":"publisher","key":"ref6","DOI":"10.1109\/CVPR52688.2022.00542"},{"doi-asserted-by":"publisher","key":"ref7","DOI":"10.1109\/CVPR52688.2022.00538"},{"doi-asserted-by":"publisher","key":"ref8","DOI":"10.1109\/ICCV48922.2021.00570"},{"key":"ref9","first-page":"15651","article-title":"Neural sparse voxel fields","volume":"33","author":"Liu","year":"2020","journal-title":"Adv. Neural Inf. Process. Syst."},{"doi-asserted-by":"publisher","key":"ref10","DOI":"10.1145\/3528223.3530127"},{"year":"2020","author":"Zhang","article-title":"NeRF++: Analyzing and improving neural radiance fields","key":"ref11"},{"doi-asserted-by":"publisher","key":"ref12","DOI":"10.1145\/3592426"},{"doi-asserted-by":"publisher","key":"ref13","DOI":"10.1111\/cgf.14022"},{"doi-asserted-by":"publisher","key":"ref14","DOI":"10.1145\/3596711.3596763"},{"doi-asserted-by":"publisher","key":"ref15","DOI":"10.1109\/ICCV51070.2023.00049"},{"doi-asserted-by":"publisher","key":"ref16","DOI":"10.1109\/CVPR.2019.00254"},{"doi-asserted-by":"publisher","key":"ref17","DOI":"10.1109\/CVPR52688.2022.01787"},{"key":"ref18","first-page":"40","article-title":"Learning representations and generative models for 3D point clouds","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Achlioptas","year":"2018"},{"doi-asserted-by":"publisher","key":"ref19","DOI":"10.1145\/3197517.3201323"},{"doi-asserted-by":"publisher","key":"ref20","DOI":"10.1109\/CVPR42600.2020.00356"},{"key":"ref21","first-page":"27171","article-title":"NeuS: Learning neural implicit surfaces by volume rendering for multi-view reconstruction","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"34","author":"Wang","year":"2021"},{"key":"ref22","first-page":"4805","article-title":"Volume rendering of neural implicit surfaces","volume":"34","author":"Yariv","year":"2021","journal-title":"Adv. Neural Inf. Process. Syst."},{"doi-asserted-by":"publisher","key":"ref23","DOI":"10.1109\/ICCV48922.2021.00580"},{"doi-asserted-by":"publisher","key":"ref24","DOI":"10.1109\/CVPR52688.2022.00536"},{"doi-asserted-by":"publisher","key":"ref25","DOI":"10.1109\/cvpr52688.2022.00538"},{"doi-asserted-by":"publisher","key":"ref26","DOI":"10.1109\/CVPR52729.2023.01201"},{"doi-asserted-by":"publisher","key":"ref27","DOI":"10.1109\/ICCV51070.2023.01811"},{"doi-asserted-by":"publisher","key":"ref28","DOI":"10.1145\/3610548.3618139"},{"doi-asserted-by":"publisher","key":"ref29","DOI":"10.1145\/3592433"},{"doi-asserted-by":"publisher","key":"ref30","DOI":"10.1109\/CVPR.2012.6248074"},{"doi-asserted-by":"publisher","key":"ref31","DOI":"10.1109\/CVPR52729.2023.00802"},{"doi-asserted-by":"publisher","key":"ref32","DOI":"10.1109\/CVPR52688.2022.00807"},{"doi-asserted-by":"publisher","key":"ref33","DOI":"10.1109\/CVPR52688.2022.01258"},{"key":"ref34","first-page":"51:1","article-title":"Switch-nerf: Learning scene decomposition with mixture of experts for large-scale neural radiance fields","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Mi","year":"2023"},{"doi-asserted-by":"publisher","key":"ref35","DOI":"10.1109\/CVPR52688.2022.00539"},{"year":"2021","author":"Mller","article-title":"Tiny-cuda-nn","key":"ref36"},{"doi-asserted-by":"publisher","key":"ref37","DOI":"10.1145\/3588432.3591516"},{"doi-asserted-by":"publisher","key":"ref38","DOI":"10.1109\/TPAMI.2022.3179507"},{"doi-asserted-by":"publisher","key":"ref39","DOI":"10.1109\/TIP.2003.819861"},{"doi-asserted-by":"publisher","key":"ref40","DOI":"10.1109\/CVPR.2018.00068"}],"container-title":["IEEE Robotics and Automation Letters"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/7083369\/10638067\/10637691.pdf?arnumber=10637691","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,1]],"date-time":"2024-09-01T04:27:22Z","timestamp":1725164842000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10637691\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10]]},"references-count":40,"journal-issue":{"issue":"10"},"URL":"https:\/\/doi.org\/10.1109\/lra.2024.3444671","relation":{},"ISSN":["2377-3766","2377-3774"],"issn-type":[{"type":"electronic","value":"2377-3766"},{"type":"electronic","value":"2377-3774"}],"subject":[],"published":{"date-parts":[[2024,10]]}}}