Paper for SG2RL@CVPR 2024 accepted_伟德国际_伟德国际1946$娱乐app游戏

Chair for Machine Learning & Computer Vision
2024-04-17T11:01:31.976411+00:00
Universit?t Augsburg

The paper "A Review and Efficient Implementation of Scene Graph Generation Metrics" by Julian Lorenz, Robin Sch?n, Katja Ludwig, and Rainer Lienhart is accepted at the Workshop on Scene Graphs and Graph Representation Learning at CVPR 2024. ? The authors review existing scene graph generation metrics and provide precise definitions that were lacking in this field. Additionally, they introduce an efficient and easy to use python package that implements all discussed metrics. To improve comparability of new scene graph generation methods, the authors provide a benchmarking service that enables an easy evaluation of scene graph generation models. ? More information can be found here: https://lorjul.github.io/sgbench/