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title
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2026-02-23 12:30:48
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NeRF-MAE: Masked AutoEncoders for Self-Supervised 3D Representation Learning for Neural Radiance Fields NeRF-MAE: Masked AutoEncoders for Self-Supervised 3D Representation Learning for Neural Radiance Fields European Conference on Computer Vision (ECCV), 2024 CVPR Neural Rendering Intelligence Workshop, 2024 Muhammad Zubair Irshad 1,2 , Sergey Zakharov 1 , Vitor Guizilini 1 , Adrien Gaidon 1 , Zsolt Kira 2 , Rares Ambrus 1 1 Toyota Research Institute 2 Georgia Tech arXiv Paper Code Presentation Dataset Narrated Video Overview: a) We present NeRF-MAE , the first large-scale self-supervised pretraining utilizing Neural Radiance Field’s (NeRF) radiance and density grid as an input modality. Our approach uses a standard 3D Swin Transformer encoder and a voxel decoder to learn a powerful representation in (a) an opacity-aware dense volumetric masked self-supervised learning objective directly in 3D . (b) Our representati...
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