March 11, 2024, 4:42 a.m. | Zhengyi Wang, Yikai Wang, Yifei Chen, Chendong Xiang, Shuo Chen, Dajiang Yu, Chongxuan Li, Hang Su, Jun Zhu

cs.LG updates on arXiv.org arxiv.org

arXiv:2403.05034v1 Announce Type: cross
Abstract: Feed-forward 3D generative models like the Large Reconstruction Model (LRM) have demonstrated exceptional generation speed. However, the transformer-based methods do not leverage the geometric priors of the triplane component in their architecture, often leading to sub-optimal quality given the limited size of 3D data and slow training. In this work, we present the Convolutional Reconstruction Model (CRM), a high-fidelity feed-forward single image-to-3D generative model. Recognizing the limitations posed by sparse 3D data, we highlight the …

abstract architecture arxiv crm cs.cv cs.lg data generative generative models however image lrm mesh quality speed transformer type

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