April 30, 2024, 4:44 a.m. | Ming Li, Pan Zhou, Jia-Wei Liu, Jussi Keppo, Min Lin, Shuicheng Yan, Xiangyu Xu

cs.LG updates on arXiv.org arxiv.org

arXiv:2311.08403v2 Announce Type: replace-cross
Abstract: Text-to-3D generation has attracted much attention from the computer vision community. Existing methods mainly optimize a neural field from scratch for each text prompt, relying on heavy and repetitive training cost which impedes their practical deployment. In this paper, we propose a novel framework for fast text-to-3D generation, dubbed Instant3D. Once trained, Instant3D is able to create a 3D object for an unseen text prompt in less than one second with a single run of …

arxiv cs.ai cs.cv cs.gr cs.lg cs.mm instant text type

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