Tri-MipRF: Tri-Mip Representation for Efficient Anti-Aliasing Neural Radiance Fields-Reference-Cited by-同舟云学术

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Tri-MipRF: Tri-Mip Representation for Efficient Anti-Aliasing Neural Radiance Fields

Published:2023-10-01 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE/CVF International Conference on Computer Vision (ICCV)
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Author:

Hu Wenbo¹,Wang Yuling¹,Ma Lin¹,Yang Bangbang¹,Gao Lin²,Liu Xiao¹,Ma Yuewen¹

Affiliation:

1. PICO, ByteDance,Beijing

2. Institute of Computing Technology, CAS

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10376473/10376477/10377265.pdf?arnumber=10377265

Cited by 11 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. AMVP: Adaptive Multi-Volume Primitives for Auto-Driving Novel View Synthesis;IEEE Robotics and Automation Letters;2024-10

2. TNDF-Fusion: Implicit Truncated Neural Distance Field for LiDAR Dense Mapping and Localization in Large Urban Environments;IEEE Robotics and Automation Letters;2024-09

3. 2D Gaussian Splatting for Geometrically Accurate Radiance Fields;Special Interest Group on Computer Graphics and Interactive Techniques Conference Conference Papers '24;2024-07-13

4. Rip-NeRF: Anti-aliasing Radiance Fields with Ripmap-Encoded Platonic Solids;Special Interest Group on Computer Graphics and Interactive Techniques Conference Conference Papers '24;2024-07-13

5. Neural Surface Reconstruction: A Game Changer for 3D Data Collection from Airborne Imagery?;IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium;2024-07-07

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