Results 11 to 20 of about 14,278 (275)
Eigengrasp-Conditioned Neural Radiance Fields
IEEE Access, 2023 In this study, we address the problem of learning a posture-controllable three-dimensional (3D) representation of articulated robotic hands. Neural radiance fields (NeRFs) have outperformed grid-like 3D representations on a novel view synthesis tasks ...
Hiroaki Aizawa, Itoshi Naramura
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Neural Articulated Radiance Field [PDF]
2021 IEEE/CVF International Conference on Computer Vision (ICCV), 2021 We present Neural Articulated Radiance Field (NARF), a novel deformable 3D representation for articulated objects learned from images. While recent advances in 3D implicit representation have made it possible to learn models of complex objects, learning pose-controllable representations of articulated objects remains a challenge, as current methods ...
Noguchi, Atsuhiro +3 more
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INITIAL ASSESSMENT ON THE USE OF STATE-OF-THE-ART NERF NEURAL NETWORK 3D RECONSTRUCTION FOR HERITAGE DOCUMENTATION [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2023 In recent decades, photogrammetry has re-emerged as a viable solution for heritage documentation. Developments in various computer vision methods have helped photogrammetry to compete against the laser scanning technology, eventually becoming ...
A. Murtiyoso, P. Grussenmeyer
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EfficientNeRF - Efficient Neural Radiance Fields
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 Neural Radiance Fields (NeRF) has been wildly applied to various tasks for its high-quality representation of 3D scenes. It takes long per-scene training time and per-image testing time. In this paper, we present EfficientNeRF as an efficient NeRF-based method to represent 3D scene and synthesize novel-view images.
Hu, Tao +4 more
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Surgical neural radiance fields from one image. [PDF]
Int J Comput Assist Radiol SurgPurpose: Neural Radiance Fields (NeRF) offer exceptional capabilities for 3D reconstruction and view synthesis, yet their reliance on extensive multi-view data limits their application in surgical intraoperative settings where only limited data is available.
Neri A +4 more
europepmc +3 more sources
Convolutional Neural Opacity Radiance Fields [PDF]
2021 IEEE International Conference on Computational Photography (ICCP), 2021 Photo-realistic modeling and rendering of fuzzy objects with complex opacity are critical for numerous immersive VR/AR applications, but it suffers from strong view-dependent brightness, color. In this paper, we propose a novel scheme to generate opacity radiance fields with a convolutional neural renderer for fuzzy objects, which is the first to ...
Luo, Haimin +6 more
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Instance Neural Radiance Field
2023 IEEE/CVF International Conference on Computer Vision (ICCV), 2023 International Conference on Computer Vision (ICCV ...
Liu, Yichen +4 more
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Nerfies: Deformable Neural Radiance Fields [PDF]
2021 IEEE/CVF International Conference on Computer Vision (ICCV), 2021 We present the first method capable of photorealistically reconstructing deformable scenes using photos/videos captured casually from mobile phones. Our approach augments neural radiance fields (NeRF) by optimizing an additional continuous volumetric deformation field that warps each observed point into a canonical 5D NeRF.
Park, Keunhong +6 more
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MMNeRF: Multi-Modal and Multi-View Optimized Cross-Scene Neural Radiance Fields
IEEE Access, 2023 We present MMNeRF, a simple yet powerful learning framework for highly photo-realistic novel view synthesis by learning Multi-modal and Multi-view features to guide neural radiance fields to a generic model.
Qi Zhang +3 more
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Self-Calibrating Neural Radiance Fields [PDF]
2021 IEEE/CVF International Conference on Computer Vision (ICCV), 2021 Accepted in ICCV21, Project Page: https://postech-cvlab.github.io/SCNeRF/
Jeong, Yoonwoo +5 more
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