all AI news
ED-NeRF: Efficient Text-Guided Editing of 3D Scene with Latent Space NeRF
March 22, 2024, 4:43 a.m. | Jangho Park, Gihyun Kwon, Jong Chul Ye
cs.LG updates on arXiv.org arxiv.org
Abstract: Recently, there has been a significant advancement in text-to-image diffusion models, leading to groundbreaking performance in 2D image generation. These advancements have been extended to 3D models, enabling the generation of novel 3D objects from textual descriptions. This has evolved into NeRF editing methods, which allow the manipulation of existing 3D objects through textual conditioning. However, existing NeRF editing techniques have faced limitations in their performance due to slow training speeds and the use of …
2d image 3d models 3d objects abstract advancement arxiv cs.ai cs.cv cs.lg diffusion diffusion models editing enabling groundbreaking image image diffusion image generation nerf novel objects performance space stat.ml text text-to-image textual type
More from arxiv.org / cs.LG updates on arXiv.org
Jobs in AI, ML, Big Data
Software Engineer for AI Training Data (School Specific)
@ G2i Inc | Remote
Software Engineer for AI Training Data (Python)
@ G2i Inc | Remote
Software Engineer for AI Training Data (Tier 2)
@ G2i Inc | Remote
Data Engineer
@ Lemon.io | Remote: Europe, LATAM, Canada, UK, Asia, Oceania
Artificial Intelligence – Bioinformatic Expert
@ University of Texas Medical Branch | Galveston, TX
Lead Developer (AI)
@ Cere Network | San Francisco, US