April 25, 2024, 7:43 p.m. | Rafael Sterzinger, Simon Brenner, Robert Sablatnig

cs.LG updates on arXiv.org arxiv.org

arXiv:2404.15903v1 Announce Type: cross
Abstract: Etruscan mirrors constitute a significant category within Etruscan art and, therefore, undergo systematic examinations to obtain insights into ancient times. A crucial aspect of their analysis involves the labor-intensive task of manually tracing engravings from the backside. Additionally, this task is inherently challenging due to the damage these mirrors have sustained, introducing subjectivity into the process. We address these challenges by automating the process through photometric-stereo scanning in conjunction with deep segmentation networks which, however, …

abstract analysis art arxiv cs.ai cs.cv cs.lg insights labor line segmentation tracing type

Lead Developer (AI)

@ Cere Network | San Francisco, US

Research Engineer

@ Allora Labs | Remote

Ecosystem Manager

@ Allora Labs | Remote

Founding AI Engineer, Agents

@ Occam AI | New York

AI Engineer Intern, Agents

@ Occam AI | US

AI Research Scientist

@ Vara | Berlin, Germany and Remote