Results 31 to 40 of about 168,620 (333)
KiloNeRF: Speeding up Neural Radiance Fields with Thousands of Tiny MLPs [PDF]
IEEE International Conference on Computer Vision, 2021 NeRF synthesizes novel views of a scene with unprecedented quality by fitting a neural radiance field to RGB images. However, NeRF requires querying a deep Multi-Layer Perceptron (MLP) millions of times, leading to slow rendering times, even on modern ...
C. Reiser +3 more
semanticscholar +1 more source
RegNeRF: Regularizing Neural Radiance Fields for View Synthesis from Sparse Inputs [PDF]
Computer Vision and Pattern Recognition, 2021 Neural Radiance Fields (NeRF) have emerged as a powerful representation for the task of novel view synthesis due to their simplicity and state-of-the-art performance.
M. Niemeyer +5 more
semanticscholar +1 more source
Ref-NeRF: Structured View-Dependent Appearance for Neural Radiance Fields [PDF]
Computer Vision and Pattern Recognition, 2021 Neural Radiance Fields (NeRF) is a popular view synthesis technique that represents a scene as a continuous volumetric function, parameterized by multilayer perceptrons that provide the volume density and view-dependent emitted radiance at each location.
Dor Verbin +5 more
semanticscholar +1 more source
NeRF-SLAM: Real-Time Dense Monocular SLAM with Neural Radiance Fields [PDF]
IEEE/RJS International Conference on Intelligent RObots and Systems, 2022 We propose a novel geometric and photometric 3D mapping pipeline for accurate and real-time scene reconstruction from casually taken monocular images.
Antoni Rosinol, J. Leonard, L. Carlone
semanticscholar +1 more source
AD-NeRF: Audio Driven Neural Radiance Fields for Talking Head Synthesis [PDF]
IEEE International Conference on Computer Vision, 2021 Generating high-fidelity talking head video by fitting with the input audio sequence is a challenging problem that receives considerable attentions recently. In this paper, we address this problem with the aid of neural scene representation networks. Our
Yudong Guo +5 more
semanticscholar +1 more source
Animatable Neural Radiance Fields for Modeling Dynamic Human Bodies [PDF]
IEEE International Conference on Computer Vision, 2021 This paper addresses the challenge of reconstructing an animatable human model from a multi-view video. Some recent works have proposed to decompose a non-rigidly deforming scene into a canonical neural radiance field and a set of deformation fields that
Sida Peng +6 more
semanticscholar +1 more source
Dense Depth Priors for Neural Radiance Fields from Sparse Input Views [PDF]
Computer Vision and Pattern Recognition, 2021 Neural radiance fields (NeRF) encode a scene into a neural representation that enables photo-realistic rendering of novel views. However, a successful reconstruction from RGB images requires a large number of input views taken under static conditions ...
Barbara Roessle +4 more
semanticscholar +1 more source
NeRSemble: Multi-view Radiance Field Reconstruction of Human Heads [PDF]
ACM Transactions on Graphics, 2023 We focus on reconstructing high-fidelity radiance fields of human heads, capturing their animations over time, and synthesizing re-renderings from novel viewpoints at arbitrary time steps.
Tobias Kirschstein +4 more
semanticscholar +1 more source
Journal of Imaging, 2018 High dynamic range (HDR) imaging techniques are nowadays widely used in building research to capture luminances in the occupant field of view and investigate visual discomfort.
Coralie Cauwerts, María Beatriz Piderit
doaj +1 more source
NeRF-Editing: Geometry Editing of Neural Radiance Fields [PDF]
Computer Vision and Pattern Recognition, 2022 Implicit neural rendering, especially Neural Radiance Field (NeRF), has shown great potential in novel view synthesis of a scene. However, current NeRF-based methods cannot enable users to perform user-controlled shape deformation in the scene.
Yu-Jie Yuan +5 more
semanticscholar +1 more source