DASNeRF: depth consistency optimization, adaptive sampling, and hierarchical structural fusion for sparse view neural radiance fields.

DASNeRF: depth consistency optimization, adaptive sampling, and hierarchical structural fusion for sparse view neural radiance fields.

To address the challenges of significant detail loss in Neural Radiance Fields (NeRF) under sparse-view input conditions, this paper proposes the DASNeRF framework. DASNeRF aims to generate high-detail novel views from a limited number of input viewpoints. To address the limitations of few-shot NeRF...

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Bibliographic Details
Main Authors: Yongshuo Zhang, Guangyuan Zhang, Kefeng Li, Zhenfang Zhu, Peng Wang, Zhenfei Wang, Chen Fu, Xiaotong Li, Zhiming Fan, Yongpeng Zhao
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2025-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0321878
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https://doi.org/10.1371/journal.pone.0321878

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