Results 61 to 70 of about 169,247 (258)

Spatiotemporal and quantitative analyses of phosphoinositides – fluorescent probe—and mass spectrometry‐based approaches

FEBS Letters, EarlyView.
Fluorescent probes allow dynamic visualization of phosphoinositides in living cells (left), whereas mass spectrometry provides high‐sensitivity, isomer‐resolved quantitation (right). Their synergistic use captures complementary aspects of lipid signaling. This review illustrates how these approaches reveal the spatiotemporal regulation and quantitative
Hiroaki Kajiho, Shin Morioka, Junko Sasaki, Takehiko Sasaki   +3 more
wiley   +1 more source

Zero-Shot 3D Scene Representation With Invertible Generative Neural Radiance Fields

IEEE Access
Generative Neural Radiance Fields (NeRFs) have recently enabled efficient synthesis of 3D scenes by training on unposed real image sets. However, existing methods for generating multi-view images of specific input images have limitations, such as ...
Kanghyeok Ko, Sungyup Kim, Minhyeok Lee
doaj   +1 more source

Towards efficient and photorealistic 3D human reconstruction: A brief survey

Visual Informatics, 2021
Reconstructing 3D digital models of humans from sensory data is a long-standing problem in computer vision and graphics with a variety of applications in VR/AR, film production, and human–computer interaction, etc.
Lu Chen, Sida Peng, Xiaowei Zhou
doaj   +1 more source

Advances in neural rendering [PDF]

ACM SIGGRAPH 2021 Courses, 2021
Tewari, A., Fried, O., Thies, J., Sitzmann, V., Lombardi, S., Xu, Z., Simon, T., Nießner, M., Tretschk, E., Liu, L., Mildenhall, B., Srinivasan, P., Pandey, R., Orts-Escolano, S., Fanello, S., Guo, M., Wetzstein, G., Zhu, J., Theobalt, C. ; https://orcid.org/0000-0001-6104-6625, Agrawala, M., Goldman, D., Zollhöfer, M.   +21 more
openaire   +2 more sources

MeshAdv: Adversarial Meshes for Visual Recognition

, 2019
Highly expressive models such as deep neural networks (DNNs) have been widely applied to various applications. However, recent studies show that DNNs are vulnerable to adversarial examples, which are carefully crafted inputs aiming to mislead the ...
Deng, Jia, Li, Bo, Liu, Mingyan, Xiao, Chaowei, Yang, Dawei   +4 more
core   +1 more source

Disordered but rhythmic—the role of intrinsic protein disorder in eukaryotic circadian timing

FEBS Letters, EarlyView.
Unstructured domains known as intrinsically disordered regions (IDRs) are present in nearly every part of the eukaryotic core circadian oscillator. IDRs enable many diverse inter‐ and intramolecular interactions that support clock function. IDR conformations are highly tunable by post‐translational modifications and environmental conditions, which ...
Emery T. Usher, Jacqueline F. Pelham
wiley   +1 more source

MVS-GS: High-Quality 3D Gaussian Splatting Mapping via Online Multi-View Stereo

IEEE Access
This study addresses the challenge of online 3D model generation for neural rendering using an RGB image stream. Previous research has tackled this issue by incorporating Neural Radiance Fields (NeRF) or 3D Gaussian Splatting (3DGS) as scene ...
Byeonggwon Lee, Junkyu Park, Khang Truong Giang, Sungho Jo, Soohwan Song   +4 more
doaj   +1 more source

Time after time – circadian clocks through the lens of oscillator theory

FEBS Letters, EarlyView.
Oscillator theory bridges physics and circadian biology. Damped oscillators require external drivers, while limit cycles emerge from delayed feedback and nonlinearities. Coupling enables tissue‐level coherence, and entrainment aligns internal clocks with environmental cues.
Marta del Olmo, Carolin Ector, Hanspeter Herzel   +2 more
wiley   +1 more source

Unsupervised learning of style-aware facial animation from real acting performances

Graphical Models, 2023
This paper presents a novel approach for text/speech-driven animation of a photo-realistic head model based on blend-shape geometry, dynamic textures, and neural rendering.
Wolfgang Paier, Anna Hilsmann, Peter Eisert   +2 more
doaj   +1 more source

Modeling Surface Appearance from a Single Photograph using Self-augmented Convolutional Neural Networks

, 2017
We present a convolutional neural network (CNN) based solution for modeling physically plausible spatially varying surface reflectance functions (SVBRDF) from a single photograph of a planar material sample under unknown natural illumination. Gathering a
Dong, Yue, Li, Xiao, Peers, Pieter, Tong, Xin   +3 more
core   +1 more source