Nerf: Neural radiance field in 3d vision, a comprehensive review

K Gao, Y Gao, H He, D Lu, L Xu, J Li - arXiv preprint arXiv:2210.00379, 2022 - arxiv.org
Neural Radiance Field (NeRF), a new novel view synthesis with implicit scene
representation has taken the field of Computer Vision by storm. As a novel view synthesis …

Advances in neural rendering

A Tewari, J Thies, B Mildenhall… - Computer Graphics …, 2022 - Wiley Online Library
Synthesizing photo‐realistic images and videos is at the heart of computer graphics and has
been the focus of decades of research. Traditionally, synthetic images of a scene are …

Sine: Semantic-driven image-based nerf editing with prior-guided editing field

C Bao, Y Zhang, B Yang, T Fan… - Proceedings of the …, 2023 - openaccess.thecvf.com
Despite the great success in 2D editing using user-friendly tools, such as Photoshop,
semantic strokes, or even text prompts, similar capabilities in 3D areas are still limited, either …

Generative neural articulated radiance fields

A Bergman, P Kellnhofer, W Yifan… - Advances in …, 2022 - proceedings.neurips.cc
Unsupervised learning of 3D-aware generative adversarial networks (GANs) using only
collections of single-view 2D photographs has very recently made much progress. These 3D …

Neumesh: Learning disentangled neural mesh-based implicit field for geometry and texture editing

B Yang, C Bao, J Zeng, H Bao, Y Zhang, Z Cui… - … on Computer Vision, 2022 - Springer
Very recently neural implicit rendering techniques have been rapidly evolved and shown
great advantages in novel view synthesis and 3D scene reconstruction. However, existing …

SPIn-NeRF: Multiview segmentation and perceptual inpainting with neural radiance fields

A Mirzaei, T Aumentado-Armstrong… - Proceedings of the …, 2023 - openaccess.thecvf.com
Abstract Neural Radiance Fields (NeRFs) have emerged as a popular approach for novel
view synthesis. While NeRFs are quickly being adapted for a wider set of applications …

D^ 2nerf: Self-supervised decoupling of dynamic and static objects from a monocular video

T Wu, F Zhong, A Tagliasacchi… - Advances in neural …, 2022 - proceedings.neurips.cc
Given a monocular video, segmenting and decoupling dynamic objects while recovering the
static environment is a widely studied problem in machine intelligence. Existing solutions …

Nerfshop: Interactive editing of neural radiance fields

C Jambon, B Kerbl, G Kopanas, S Diolatzis… - Proceedings of the …, 2023 - inria.hal.science
Neural Radiance Fields (NeRFs) have revolutionized novel view synthesis for captured
scenes, with recent methods allowing interactive free-viewpoint navigation and fast training …

Reference-guided controllable inpainting of neural radiance fields

A Mirzaei, T Aumentado-Armstrong… - Proceedings of the …, 2023 - openaccess.thecvf.com
Abstract The popularity of Neural Radiance Fields (NeRFs) for view synthesis has led to a
desire for NeRF editing tools. Here, we focus on inpainting regions in a view-consistent and …

Omniavatar: Geometry-guided controllable 3d head synthesis

H Xu, G Song, Z Jiang, J Zhang, Y Shi… - Proceedings of the …, 2023 - openaccess.thecvf.com
We present OmniAvatar, a novel geometry-guided 3D head synthesis model trained from in-
the-wild unstructured images that is capable of synthesizing diverse identity-preserved 3D …