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InsertNeRF: Instilling Generalizability into NeRF with HyperNet Modules
March 26, 2024, 4:48 a.m. | Yanqi Bao, Tianyu Ding, Jing Huo, Wenbin Li, Yuxin Li, Yang Gao
cs.CV updates on arXiv.org arxiv.org
Abstract: Generalizing Neural Radiance Fields (NeRF) to new scenes is a significant challenge that existing approaches struggle to address without extensive modifications to vanilla NeRF framework. We introduce InsertNeRF, a method for INStilling gEneRalizabiliTy into NeRF. By utilizing multiple plug-and-play HyperNet modules, InsertNeRF dynamically tailors NeRF's weights to specific reference scenes, transforming multi-scale sampling-aware features into scene-specific representations. This novel design allows for more accurate and efficient representations of complex appearances and geometries. Experiments show that …
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