Search Results for author:
Found 7 papers, 1 papers with code
RefFusion: Reference Adapted Diffusion Models for 3D Scene Inpainting
In this work, we propose an approach for 3D scene inpainting -- the task of coherently replacing parts of the reconstructed scene with desired content.
Reconstructive Latent-Space Neural Radiance Fields for Efficient 3D Scene Representations
The resulting latent-space NeRF can produce novel views with higher quality than standard colour-space NeRFs, as the AE can correct certain visual artifacts, while rendering over three times faster.
Watch Your Steps: Local Image and Scene Editing by Text Instructions
A field is trained on relevance maps of training views, denoted as the relevance field, defining the 3D region within which modifications should be made.
Reference-guided Controllable Inpainting of Neural Radiance Fields
The popularity of Neural Radiance Fields (NeRFs) for view synthesis has led to a desire for NeRF editing tools.
CAMM: Building Category-Agnostic and Animatable 3D Models from Monocular Videos
Animating an object in 3D often requires an articulated structure, e. g. a kinematic chain or skeleton of the manipulated object with proper skinning weights, to obtain smooth movements and surface deformations.
SPIn-NeRF: Multiview Segmentation and Perceptual Inpainting with Neural Radiance Fields
We refer to this task as 3D inpainting.
LaTeRF: Label and Text Driven Object Radiance Fields
In this paper we introduce LaTeRF, a method for extracting an object of interest from a scene given 2D images of the entire scene, known camera poses, a natural language description of the object, and a set of point-labels of object and non-object points in the input images.
