Li Fang — accepted AI-conference papers

2025

Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction

Li Fang, Hao Zhu, Longlong Chen, Fei Hu, Long Ye, Zhan Ma

CVPR 2025poster

Recent advancements in generalizable novel view synthesis have achieved impressive quality through interpolation between nearby views. However, rendering high-resolution images remains computationally intensive due to the need for dense sampling of all rays. Recognizing that natural scenes are typic…

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2025

GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis

You Wang, Li Fang, Hao Zhu, Fei Hu, Long Ye, Zhan Ma

CVPR 2025poster

Neural Radiance Fields (NeRF) have transformed novel view synthesis by modeling scene-specific volumetric representations directly from images. While generalizable NeRF models can generate novel views across unknown scenes by learning latent ray representations, their performance heavily depends on…

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