March 28, 2024, 4:45 a.m. | Qiuhong Shen, Xuanyu Yi, Zike Wu, Pan Zhou, Hanwang Zhang, Shuicheng Yan, Xinchao Wang

cs.CV updates on arXiv.org arxiv.org

arXiv:2403.18795v1 Announce Type: new
Abstract: We tackle the challenge of efficiently reconstructing a 3D asset from a single image with growing demands for automated 3D content creation pipelines. Previous methods primarily rely on Score Distillation Sampling (SDS) and Neural Radiance Fields (NeRF). Despite their significant success, these approaches encounter practical limitations due to lengthy optimization and considerable memory usage. In this report, we introduce Gamba, an end-to-end amortized 3D reconstruction model from single-view images, emphasizing two main insights: (1) 3D …

3d reconstruction abstract arxiv automated challenge cs.ai cs.cv distillation fields image mamba nerf neural radiance fields pipelines sampling success type view

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