DiVa-360: The Dynamic Visual Dataset for Immersive Neural Fields

Lu, C-Y; Zhou, P; Xing, A; Pokhariya, C; Dey, A; Shah, IN; Mavidipalli, R; Hu, D; Comport, AI; Chen, K; Sridhar, S

DiVa-360: The Dynamic Visual Dataset for Immersive Neural Fields

Lu, C-Y Zhou, P Xing, A Pokhariya, C Dey, A Shah, IN Mavidipalli, R Hu, D Comport, AI Chen, K Sridhar, S

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Publisher:: IEEE
Publication Type:: Conference Proceeding
Citation:: 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024, abs/2103.02597, pp. 22466-22476
Issue Date:: 2024-06-16

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Field	Value	Language
dc.contributor.author	Lu, C-Y
dc.contributor.author	Zhou, P
dc.contributor.author	Xing, A
dc.contributor.author	Pokhariya, C
dc.contributor.author	Dey, A
dc.contributor.author	Shah, IN
dc.contributor.author	Mavidipalli, R
dc.contributor.author	Hu, D
dc.contributor.author	Comport, AI
dc.contributor.author	Chen, K
dc.contributor.author	Sridhar, S
dc.date	2024-06-16
dc.date.accessioned	2024-10-03T04:01:46Z
dc.date.available	2024-10-03T04:01:46Z
dc.date.issued	2024-06-16
dc.identifier.citation	2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024, abs/2103.02597, pp. 22466-22476
dc.identifier.uri	http://hdl.handle.net/10453/181160
dc.language	en
dc.publisher	IEEE
dc.relation.ispartof	2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
dc.relation.ispartof	2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
dc.relation.isbasedon	10.1109/cvpr52733.2024.02120
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	DiVa-360: The Dynamic Visual Dataset for Immersive Neural Fields
dc.type	Conference Proceeding
utslib.citation.volume	abs/2103.02597
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	closed_access	*
dc.date.updated	2024-10-03T04:01:38Z
pubs.finish-date	2024-06-22
pubs.publication-status	Published
pubs.start-date	2024-06-16
pubs.volume	abs/2103.02597

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http://hdl.handle.net/10453/181160