Zobrazeno 1 - 10
of 1 191
pro vyhledávání: '"Li, LingZhi"'
Recently, permissioned blockchain has been extensively explored in various fields, such as asset management, supply chain, healthcare, and many others. Many scholars are dedicated to improving its verifiability, scalability, and performance based on
Externí odkaz:
http://arxiv.org/abs/2311.02582
We present a novel method for reconstructing clothed humans from a sparse set of, e.g., 1 to 6 RGB images. Despite impressive results from recent works employing deep implicit representation, we revisit the volumetric approach and demonstrate that be
Externí odkaz:
http://arxiv.org/abs/2307.13282
Reconstructing neural radiance fields with explicit volumetric representations, demonstrated by Plenoxels, has shown remarkable advantages on training and rendering efficiency, while grid-based representations typically induce considerable overhead f
Externí odkaz:
http://arxiv.org/abs/2305.18163
Image colorization is a challenging problem due to multi-modal uncertainty and high ill-posedness. Directly training a deep neural network usually leads to incorrect semantic colors and low color richness. While transformer-based methods can deliver
Externí odkaz:
http://arxiv.org/abs/2212.11613
In this paper, we present a novel and effective framework, named 4K-NeRF, to pursue high fidelity view synthesis on the challenging scenarios of ultra high resolutions, building on the methodology of neural radiance fields (NeRF). The rendering proce
Externí odkaz:
http://arxiv.org/abs/2212.04701
Approximating radiance fields with volumetric grids is one of promising directions for improving NeRF, represented by methods like Plenoxels and DVGO, which achieve super-fast training convergence and real-time rendering. However, these methods typic
Externí odkaz:
http://arxiv.org/abs/2211.16386
We present an explicit-grid based method for efficiently reconstructing streaming radiance fields for novel view synthesis of real world dynamic scenes. Instead of training a single model that combines all the frames, we formulate the dynamic modelin
Externí odkaz:
http://arxiv.org/abs/2210.14831
Autor:
Guan, Yiran, Zhang, Jiejun, Li, Lingzhi, Cao, Ruidong, Wang, Guangying, Chen, Jingxu, Yao, Jianping
The synthetic dimension opens new horizons in quantum physics and topological photonics by enabling new dimensions for field and particle manipulations. The most appealing property of the photonic synthetic dimension is its ability to emulate high-di
Externí odkaz:
http://arxiv.org/abs/2208.11901
Publikováno v:
In Journal of Building Engineering 15 October 2024 95
Publikováno v:
In Journal of Molecular Structure 15 September 2024 1312 Part 1