PatentNet: A Large-Scale Incomplete Multiview, Multimodal, Multilabel Industrial Goods Image Database

TL;DR

PatentNet is a comprehensive large-scale industrial goods image dataset with diverse, multimodal, and multilabel annotations, sourced from design patents, enabling advanced research in image classification, retrieval, and clustering.

Contribution

This paper introduces PatentNet, the first extensive industrial goods image database with incomplete multiview, multimodal, and multilabel data, surpassing previous datasets in diversity and complexity.

Findings

PatentNet contains over 6 million images and texts.

It organizes images into 32 classes and 219 subclasses.

Experiments show PatentNet's higher diversity and challenge level.

Abstract

In deep learning area, large-scale image datasets bring a breakthrough in the success of object recognition and retrieval. Nowadays, as the embodiment of innovation, the diversity of the industrial goods is significantly larger, in which the incomplete multiview, multimodal and multilabel are different from the traditional dataset. In this paper, we introduce an industrial goods dataset, namely PatentNet, with numerous highly diverse, accurate and detailed annotations of industrial goods images, and corresponding texts. In PatentNet, the images and texts are sourced from design patent. Within over 6M images and corresponding texts of industrial goods labeled manually checked by professionals, PatentNet is the first ongoing industrial goods image database whose varieties are wider than industrial goods datasets used previously for benchmarking. PatentNet organizes millions of images into 32 classes and 219 subclasses based on the Locarno Classification Agreement. Through extensive experiments on image classification, image retrieval and incomplete multiview clustering, we demonstrate that our PatentNet is much more diverse, complex, and challenging, enjoying higher potentials than existing industrial image datasets. Furthermore, the characteristics of incomplete multiview, multimodal and multilabel in PatentNet are able to offer unparalleled opportunities in the artificial intelligence community and beyond.