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SpiNeRF: direct-trained spiking neural networks for efficient neural radiance field rendering [PDF]
Frontiers in NeuroscienceSpiking neural networks (SNNs) have recently demonstrated significant progress across various computational tasks, due to their potential for energy efficiency.
Xingting Yao +11 more
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Trends and Techniques in 3D Reconstruction and Rendering: A Survey with Emphasis on Gaussian Splatting [PDF]
SensorsThree-Dimensional Gaussian Splatting (3DGS), an important advancement in the field of computer graphics and 3D vision, has emerged to greatly accelerate the rendering process in novel views’ synthesis. Due to its ability to directly realize the real-time
Wenhe Chen +4 more
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Neural Lumigraph Rendering [PDF]
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021 Project website: http://www.computationalimaging.org/publications/nlr/
Kellnhofer, Petr +5 more
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UniRender: Reconstructing 3D Surfaces from Aerial Images with a Unified Rendering Scheme
Remote Sensing, 2023 While recent advances in the field of neural rendering have shown impressive 3D reconstruction performance, it is still a challenge to accurately capture the appearance and geometry of a scene by using neural rendering, especially for remote sensing ...
Yiming Yan +3 more
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IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 Project page with code and videos at https://light-field-neural-rendering.github ...
Mohammed Suhail +3 more
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Mathematics, 2023 In the rapidly emerging era of untact (“contact-free”) technologies, the requirement for three-dimensional (3D) virtual environments utilized in virtual reality (VR)/augmented reality (AR) and the metaverse has seen significant growth, owing to their ...
Jisun Park, Kyungeun Cho
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ACM Transactions on Graphics, 2019 The modern computer graphics pipeline can synthesize images at remarkable visual quality; however, it requires well-defined, high-quality 3D content as input. In this work, we explore the use of imperfect 3D content, for instance, obtained from photo-metric reconstructions with noisy and incomplete surface geometry, while still aiming to ...
Thies, Justus +2 more
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Agronomy, 2023 The application of 3D digital models to high-throughput plant phenotypic analysis is a research hotspot nowadays. Traditional methods, such as manual measurement and laser scanning, have high costs, and multi-view, unsupervised reconstruction methods are
Hui Liu +6 more
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Neural Scene De-rendering [PDF]
2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017 We study the problem of holistic scene understanding. We would like to obtain a compact, expressive, and interpretable representation of scenes that encodes information such as the number of objects and their categories, poses, positions, etc. Such a representation would allow us to reason about and even reconstruct or manipulate elements of the scene.
Wu, Jiajun +2 more
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BokehMe: When Neural Rendering Meets Classical Rendering
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 We propose BokehMe, a hybrid bokeh rendering framework that marries a neural renderer with a classical physically motivated renderer. Given a single image and a potentially imperfect disparity map, BokehMe generates high-resolution photo-realistic bokeh effects with adjustable blur size, focal plane, and aperture shape.
Peng, Juewen +5 more
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