The Large Labelled Logo Dataset (L3D): A Multipurpose and Hand-Labelled Continuously Growing Dataset
This dataset addresses a problem for researchers and practitioners in computer vision and intellectual property by providing a continuously growing, multipurpose resource, though it is incremental as it builds on existing classification systems.
The authors tackled the lack of a large, hand-labelled dataset for logo analysis by creating the Large Labelled Logo Dataset (L3D), which includes around 770k color images with multiple labels based on the Vienna classification, and they demonstrated its utility for logo classification and generation.
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.