Nerf: Neural radiance field in 3d vision, a comprehensive review
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 …
representation has taken the field of Computer Vision by storm. As a novel view synthesis …
Advances in neural rendering
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 …
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
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 …
semantic strokes, or even text prompts, similar capabilities in 3D areas are still limited, either …
Generative neural articulated radiance fields
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 …
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
Very recently neural implicit rendering techniques have been rapidly evolved and shown
great advantages in novel view synthesis and 3D scene reconstruction. However, existing …
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 …
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 …
static environment is a widely studied problem in machine intelligence. Existing solutions …
Nerfshop: Interactive editing of neural radiance fields
Neural Radiance Fields (NeRFs) have revolutionized novel view synthesis for captured
scenes, with recent methods allowing interactive free-viewpoint navigation and fast training …
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 …
desire for NeRF editing tools. Here, we focus on inpainting regions in a view-consistent and …
Omniavatar: Geometry-guided controllable 3d head synthesis
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 …
the-wild unstructured images that is capable of synthesizing diverse identity-preserved 3D …