Results 21 to 30 of about 90,914 (336)
Robust Dynamic Radiance Fields [PDF]
Computer Vision and Pattern Recognition, 2023 Dynamic radiance field reconstruction methods aim to model the time-varying structure and appearance of a dynamic scene. Existing methods, however, assume that accurate camera poses can be reliably estimated by Structure from Motion (SfM) algorithms ...
Y. Liu +8 more
semanticscholar +1 more source
Point-NeRF: Point-based Neural Radiance Fields [PDF]
Computer Vision and Pattern Recognition, 2022 Volumetric neural rendering methods like NeRF [34] generate high-quality view synthesis results but are optimized per-scene leading to prohibitive reconstruction time.
Qiangeng Xu +6 more
semanticscholar +1 more source
Spiritus: A Journal of Christian Spirituality, 2014 Citation: 'radiance' in the IUPAC Compendium of Chemical Terminology, 3rd ed.; International Union of Pure and Applied Chemistry; 2006. Online version 3.0.1, 2019. 10.1351/goldbook.R05037 • License: The IUPAC Gold Book is licensed under Creative Commons Attribution-ShareAlike CC BY-SA 4.0 International for individual terms.
Fabian Langguth, Michael Goesele
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Fast Dynamic Radiance Fields with Time-Aware Neural Voxels [PDF]
ACM SIGGRAPH Conference and Exhibition on Computer Graphics and Interactive Techniques in Asia, 2022 Neural radiance fields (NeRF) have shown great success in modeling 3D scenes and synthesizing novel-view images. However, most previous NeRF methods take much time to optimize one single scene. Explicit data structures, e.g.
Jiemin Fang +7 more
semanticscholar +1 more source
Temporal radiance caching [PDF]
ACM SIGGRAPH 2006 Sketches on - SIGGRAPH '06, 2006 We present a novel method for fast, high quality computation of glossy global illumination in animated environments. Building on the irradiance caching and radiance caching algorithms, our method leverages temporal coherence by sparse temporal sampling and interpolation of the indirect lighting. In our approach, part of the global illumination solution
Gautron, Pascal +2 more
openaire +6 more sources
NoPe-NeRF: Optimising Neural Radiance Field with No Pose Prior [PDF]
Computer Vision and Pattern Recognition, 2022 Training a Neural Radiance Field (NeRF) without precomputed camera poses is challenging. Recent advances in this direction demonstrate the possibility of jointly optimising a NeRF and camera poses in forward-facing scenes.
Wen-Jing Bian +4 more
semanticscholar +1 more source
Solution of topical spectroradiometric problems using synchrotron radiation
Российский технологический журнал, 2022 Objectives. In order to solve fundamental metrological problems concerning the reproduction and transmission of spectral radiometry units, as well as developing methods and tools for metrological support of modern technologies such as ...
A. S. Sigov +5 more
doaj +1 more source
NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collections [PDF]
Computer Vision and Pattern Recognition, 2020 We present a learning-based method for synthesizing novel views of complex scenes using only unstructured collections of in-the-wild photographs. We build on Neural Radiance Fields (NeRF), which uses the weights of a multi-layer perceptron to model the ...
Ricardo Martin-Brualla +5 more
semanticscholar +1 more source
NeRF2: Neural Radio-Frequency Radiance Fields [PDF]
ACM/IEEE International Conference on Mobile Computing and Networking, 2023 Although Maxwell discovered the physical laws of electromagnetic waves 160 years ago, how to precisely model the propagation of an RF signal in an electrically large and complex environment remains a long-standing problem.
Xiaopeng Zhao +3 more
semanticscholar +1 more source
BARF: Bundle-Adjusting Neural Radiance Fields [PDF]
IEEE International Conference on Computer Vision, 2021 Neural Radiance Fields (NeRF) [31] have recently gained a surge of interest within the computer vision community for its power to synthesize photorealistic novel views of real-world scenes.
Chen-Hsuan Lin +3 more
semanticscholar +1 more source