all AI news
ViFu: Multiple 360$^\circ$ Objects Reconstruction with Clean Background via Visible Part Fusion
April 16, 2024, 4:47 a.m. | Tianhan Xu, Takuya Ikeda, Koichi Nishiwaki
cs.CV updates on arXiv.org arxiv.org
Abstract: In this paper, we propose a method to segment and recover a static, clean background and multiple 360$^\circ$ objects from observations of scenes at different timestamps. Recent works have used neural radiance fields to model 3D scenes and improved the quality of novel view synthesis, while few studies have focused on modeling the invisible or occluded parts of the training images. These under-reconstruction parts constrain both scene editing and rendering view selection, thereby limiting their …
3d scenes abstract arxiv cs.cv fields fusion multiple neural radiance fields novel objects paper part quality segment type via
More from arxiv.org / cs.CV 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