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

Asier Gutiérrez-Fandiño, David Pérez-Fernández, Jordi Armengol-Estapé

2021-12-10Image Classification Classification

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.

Results

Task	Dataset	Metric	Value	Model
Image Classification	Large Labelled Logo Dataset (L3D)	Eval F1	0.2786	L3D_original_2level
Image Classification	Large Labelled Logo Dataset (L3D)	Eval F1	0.1155	L3D_original_3level

Related Papers

Automatic Classification and Segmentation of Tunnel Cracks Based on Deep Learning and Visual Explanations2025-07-18 Adversarial attacks to image classification systems using evolutionary algorithms2025-07-17 Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy2025-07-17 Federated Learning for Commercial Image Sources2025-07-17 MUPAX: Multidimensional Problem Agnostic eXplainable AI2025-07-17 Efficient Calisthenics Skills Classification through Foreground Instance Selection and Depth Estimation2025-07-16 Safeguarding Federated Learning-based Road Condition Classification2025-07-16 Hashed Watermark as a Filter: Defeating Forging and Overwriting Attacks in Weight-based Neural Network Watermarking2025-07-15