Results 21 to 30 of about 2,209 (160)
CoNeRF: Controllable Neural Radiance Fields
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 We extend neural 3D representations to allow for intuitive and interpretable user control beyond novel view rendering (i.e. camera control). We allow the user to annotate which part of the scene one wishes to control with just a small number of mask annotations in the training images. Our key idea is to treat the attributes as latent variables that are
Kania, Kacper +4 more
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Cross-Spectral Neural Radiance Fields
2022 International Conference on 3D Vision (3DV), 2022 We propose X-NeRF, a novel method to learn a Cross-Spectral scene representation given images captured from cameras with different light spectrum sensitivity, based on the Neural Radiance Fields formulation. X-NeRF optimizes camera poses across spectra during training and exploits Normalized Cross-Device Coordinates (NXDC) to render images of different
Matteo Poggi +5 more
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D-NeRF: Neural Radiance Fields for Dynamic Scenes [PDF]
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021 Neural rendering techniques combining machine learning with geometric reasoning have arisen as one of the most promising approaches for synthesizing novel views of a scene from a sparse set of images. Among these, stands out the Neural radiance fields (NeRF), which trains a deep network to map 5D input coordinates (representing spatial location and ...
Pumarola Peris, Albert +3 more
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Locally Stylized Neural Radiance Fields
2023 IEEE/CVF International Conference on Computer Vision (ICCV), 2023 ICCV ...
Pang, Hong-Wing +2 more
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MarkNerf:Watermarking for Neural Radiance Field
, 2023 A watermarking algorithm is proposed in this paper to address the copyright protection issue of implicit 3D models. The algorithm involves embedding watermarks into the images in the training set through an embedding network, and subsequently utilizing the NeRF model for 3D modeling.
Chen, Lifeng +5 more
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Self-Evolving Neural Radiance Fields
, 2023 Recently, neural radiance field (NeRF) has shown remarkable performance in novel view synthesis and 3D reconstruction. However, it still requires abundant high-quality images, limiting its applicability in real-world scenarios. To overcome this limitation, recent works have focused on training NeRF only with sparse viewpoints by giving additional ...
Jung, Jaewoo +5 more
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PyNeRF: Pyramidal Neural Radiance Fields
, 2023 Neural Radiance Fields (NeRFs) can be dramatically accelerated by spatial grid representations. However, they do not explicitly reason about scale and so introduce aliasing artifacts when reconstructing scenes captured at different camera distances. Mip-NeRF and its extensions propose scale-aware renderers that project volumetric frustums rather than ...
Turki, Haithem +3 more
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Acceleration Approach for Neural Radiance Field in Dynamic 3D Human Reconstruction [PDF]
Jisuanji gongchengThis study proposes a novel acceleration method for the Neural Radiance Field (NeRF) in dynamic 3D human reconstruction to address the challenges of low training efficiency and high computational complexity in volume rendering.
XIAO Yilong, DENG Yiqin, CHEN Zhigang
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Buildings, 2023 For the surface defects inspection task, operators need to check the defect in local detail images by specifying the location, which only the global 3D model reconstruction can’t satisfy.
Kunlong Hong +2 more
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Neural Radiance Field for Human Reconstruction Based on Multi-scale Hierarchical Network [PDF]
Jisuanji kexueThe reconstruction of 3D human models from monocular RGB video faces challenges in accurately capturing human poses,especially when using prior models like SMPL.Due to its rigid assumptions,such models struggle to depict subtle pose variations,leading to
WANG Yang, WANG Guodong, ZHAO Junli, SHENG Xiaomeng
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