Results 141 to 150 of about 4,408 (223)

NeRF-Texture: Texture Synthesis with Neural Radiance Fields

Special Interest Group on Computer Graphics and Interactive Techniques Conference Conference Proceedings, 2023
Yihua Huang 0002, Yan-Pei Cao, Yu-Kun Lai, Ying Shan, Lin Gao 0004   +4 more
openaire   +1 more source

IVAH: Invisible-Region Augmented Human Rendering From Monocular Images

IEEE Access
Most neural radiance field (NeRF)-based human rendering methods rely on per-subject optimization or multi-view data input to reconstruct the 3D radiance field of human subjects.
Do Yeop Kim, Ju Yong Chang
doaj   +1 more source

NeRF-Aug: Data Augmentation for Robotics with Neural Radiance Fields

CoRR
Training a policy that can generalize to unknown objects is a long standing challenge within the field of robotics. The performance of a policy often drops significantly in situations where an object in the scene was not seen during training. To solve this problem, we present NeRF-Aug, a novel method that is capable of teaching a policy to interact ...
Eric Zhu, Mara Levy, Matthew Gwilliam, Abhinav Shrivastava   +3 more
openaire   +2 more sources

Neural Radiance Field-based Visual Rendering: A Comprehensive Review

In recent years, Neural Radiance Fields (NeRF) has made remarkable progress in the field of computer vision and graphics, providing strong technical support for solving key tasks including 3D scene understanding, new perspective synthesis, human body ...
Huo, Yukang, Ran, Yang, Tian, Qingbin, Wang, Haihua, Wang, Ruifeng, Yao, Mingyuan   +5 more
core  

Instant HDR-NeRF: Fast Learning Of High Dynamic Range View Synthesis With Unknown Exposure Settings [PDF]

We propose Instant High Dynamic Range Neural Radiance Fields (Instant HDR-NeRF), a method of learning high dynamic range (HDR) view synthesis from a set of low dynamic range (LDR) views with unknown and varying exposure and white balance in as little as ...
Nguyen, Nam
core  

NeRF in Robotics: A Survey

Meticulous 3D environment representations have been a longstanding goal in computer vision and robotics fields. The recent emergence of neural implicit representations has introduced radical innovation to this field as implicit representations enable ...
Liu, Shaohui, Miao, Yanzi, Pan, Lei, Peng, Songyou, Pollefeys, Marc, Tomizuka, Masayoshi, Wang, Guangming, Wang, Hesheng, Xu, Chenfeng, Zhan, Wei   +9 more
core  

WaterHE-NeRF: Water-ray Tracing Neural Radiance Fields for Underwater Scene Reconstruction

Neural Radiance Field (NeRF) technology demonstrates immense potential in novel viewpoint synthesis tasks, due to its physics-based volumetric rendering process, which is particularly promising in underwater scenes. Addressing the limitations of existing
He, Zongxin, Liang, Tianyu, Zhang, Dehuan, Zhou, Jingchun   +3 more
core  

A benchmark dataset for objective quality assessment of view synthesis for neural radiance field (NeRF). [PDF]

Data Brief
Onuoha C, Luo S, Flaherty J, Huong TT, Nam PN, Thang TC.   +5 more
europepmc   +1 more source

Neural Radiance Fields: Past, Present, and Future

The various aspects like modeling and interpreting 3D environments and surroundings have enticed humans to progress their research in 3D Computer Vision, Computer Graphics, and Machine Learning.
Mittal, Ansh
core  

ARS-GS: Anisotropic Reflective Spherical 3D Gaussian Splatting. [PDF]

J Imaging
Wu C, Shi X, Chu Z, Huang Y.
europepmc   +1 more source