Logo Recognition

A large-scale logo image database for logo detection and brand recognition from real-world product images. Source: LOGO-Net: Large-scale Deep Logo Detection and Brand Recognition with Deep Region-based Convolutional Networks

Open Set Logo Detection Dataset (OSLD Dataset) is a dataset of eCommerce product images with associated brand logo images. It is released under creative commons (CC BY-NC 4.0) license to promote research in open set logo detection. The dataset can be used only for research purposes. The dataset contains: - 20K eCommerce product images, with logo bounding box annotations - 12.1K logo classes with 20.8K canonical logo images - Product image logo bounding box to canonical logo image match pair annotations Image source: https://arxiv.org/pdf/1911.07440.pdf

The Wikidata Reference Logo Dataset (WiRLD), a comprehensive collection of reference logos specifically designed to address the challenges of large-scale logo identification. Recognizing the limitations of existing logo datasets, which often have a restricted number of logo classes or lack public availability, the authors curated WiRLD to facilitate research on more realistic, large-scale logo identification tasks. WiRLD contains 100,000 reference logo images sourced from Wikidata, representing 100,000 distinct logo classes. Each entity in the dataset has one corresponding logo image. The dataset's focus on providing a vast and readily accessible collection of reference logos makes it particularly valuable for evaluating one-shot logo identification methods, especially in large-scale scenarios

The Wikidata Reference Logo Dataset (WiRLD), a comprehensive collection of reference logos specifically designed to address the challenges of large-scale logo identification. Recognizing the limitations of existing logo datasets, which often have a restricted number of logo classes or lack public availability, the authors curated WiRLD to facilitate research on more realistic, large-scale logo identification tasks. WiRLD contains 100,000 reference logo images sourced from Wikidata, representing 100,000 distinct logo classes. Each entity in the dataset has one corresponding logo image. The dataset's focus on providing a vast and readily accessible collection of reference logos makes it particularly valuable for evaluating one-shot logo identification methods, especially in large-scale scenarios.

Introduction The dataset consists of Indian traffic signs images for classification and detection. The images have been taken in varied weather conditions in daylight, evening and nights. The dataset has a wide variety of variations of illumination, distances, view points etc. This dataset represents a very challenging set of unstructured images of Indian traffic signboards. ### Dataset Features - Captured by 2000+ unique users - Covers wide variety of Indian traffic signs - Captured with 20+ cities accross India - Captured using mobile phones - Highly diverse - Various lighting conditions like day, night, - Outdoor scene with variety of view points ### Dataset Features - Classification and detection annotations available - Multiple category annotations possible - COCO, PASCAL VOC and YOLO formats To download full datasets or to submit a request for your dataset needs, please ping us at sales@datacluster.ai Visit www.datacluster.ai to know more. Note: All the images are manually captured and verified by a large contributor base on DataCluster platform