LP-DIF: Learning Local Pattern-Specific Deep Implicit Function for 3D Objects and Scenes
Meng Wang, Yu-Shen Liu, Yue Gao, Kanle Shi, Yi Fang, Zhizhong Han
2023年份
7顶会引用
摘要
ing. Our LP-DIF can restore more geometry details, and thus improve the quality of 3D reconstruction. Experiments demonstrate that our method can achieve the state-of-theart performance over previous methods. Code is available at https://github.com/gtyxyz/lpdif .
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引用它的顶会 Paper7
- Learning Signed Distance Functions from Noisy 3D Point Clouds via Noise to Noise MappingBaorui Ma, Yu-Shen Liu, Zhizhong HanICML 2023 · 被引用 35 次
- GridPull: Towards Scalability in Learning Implicit Representations from 3D Point CloudsChao Chen, Yu-Shen Liu, Zhizhong HanICCV 2023 · 被引用 19 次
- Towards Croppable Implicit Neural RepresentationsMaor Ashkenazi, Eran TreisterNeurIPS 2024 · 被引用 6 次
- MoRIC: A Modular Region-based Implicit Codec for Image CompressionGen Li, Haotian Wu, Deniz GündüzNeurIPS 2025 · 被引用 5 次
- Behind the Veil: Enhanced Indoor 3D Scene Reconstruction with Occluded Surfaces CompletionSu Sun, Cheng Zhao, Yuliang Guo, Ruoyu Wang 等CVPR 2024 · 被引用 3 次
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