April 16, 2024, 4:44 a.m. | Julian Lorenz, Robin Sch\"on, Katja Ludwig, Rainer Lienhart

cs.LG updates on arXiv.org arxiv.org

arXiv:2404.09616v1 Announce Type: cross
Abstract: Scene graph generation has emerged as a prominent research field in computer vision, witnessing significant advancements in the recent years. However, despite these strides, precise and thorough definitions for the metrics used to evaluate scene graph generation models are lacking. In this paper, we address this gap in the literature by providing a review and precise definition of commonly used metrics in scene graph generation. Our comprehensive examination clarifies the underlying principles of these metrics …

abstract arxiv computer computer vision cs.cv cs.lg definitions graph however implementation metrics paper research review type vision

Founding AI Engineer, Agents

@ Occam AI | New York

AI Engineer Intern, Agents

@ Occam AI | US

AI Research Scientist

@ Vara | Berlin, Germany and Remote

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne