The Large Labelled Logo Dataset (L3D): A Multipurpose and Hand-Labelled Continuously Growing Dataset

TL;DR

The paper introduces L3D, a large, hand-labelled, continuously expanding logo dataset with 770,000 images, designed for logo classification and generation tasks, leveraging hierarchical annotations from EUIPO.

Contribution

It provides a novel, extensive, and hierarchically annotated logo dataset that supports multiple applications like classification and generation.

Findings

Dataset contains 770,000 images with hierarchical labels.

Supports logo classification and generation tasks.

Enables research with a large, continuously growing dataset.

Abstract

In this work, we present the Large Labelled Logo Dataset (L3D), a multipurpose, hand-labelled, continuously growing dataset. It is composed of around 770k of color 256x256 RGB images extracted from the European Union Intellectual Property Office (EUIPO) open registry. Each of them is associated to multiple labels that classify the figurative and textual elements that appear in the images. These annotations have been classified by the EUIPO evaluators using the Vienna classification, a hierarchical classification of figurative marks. We suggest two direct applications of this dataset, namely, logo classification and logo generation.