A Retail Product Categorisation Dataset
Most eCommerce applications, like web-shops have millions of products. In this context, the identification of similar products is a common sub-task, which can be utilized in the implementation of recommendation systems, product search engines and internal supply logistics. Providing this data set, our goal is to boost the evaluation of machine learning methods for the prediction of the category of the retail products from tuples of images and descriptions.
Code (1)
Tasks
BIG-bench Machine LearningRecommendation SystemsSimilar Papers 제목 키워드 기반
RP2K: A Large-Scale Retail Product Dataset for Fine-Grained Image Classification
We introduce RP2K, a new large-scale retail product dataset for fine-grained image classification. Unlike previous datasets focusing on relatively few products, we collect more than 500,000 images of retail products on s…
Fine-Grained Image ClassificationGeneral Classificationimage-classificationImage Classification+3Bag of Tricks for Retail Product Image Classification
Retail Product Image Classification is an important Computer Vision and Machine Learning problem for building real world systems like self-checkout stores and automated retail execution evaluation. In this work, we prese…
ClassificationGeneral Classificationimage-classificationImage ClassificationUsing Contrastive Learning and Pseudolabels to learn representations for Retail Product Image Classification
Retail product Image classification problems are often few shot classification problems, given retail product classes cannot have the type of variations across images like a cat or dog or tree could have. Previous works …
ClassificationContrastive Learningimage-classificationImage Classification+1Exploring Fine-grained Retail Product Discrimination with Zero-shot Object Classification Using Vision-Language Models
In smart retail applications, the large number of products and their frequent turnover necessitate reliable zero-shot object classification methods. The zero-shot assumption is essential to avoid the need for re-training…
ClassificationDimensionality ReductionUnitail: Detecting, Reading, and Matching in Retail Scene
To make full use of computer vision technology in stores, it is required to consider the actual needs that fit the characteristics of the retail scene. Pursuing this goal, we introduce the United Retail Datasets (Unitail…
BenchmarkingDense Object DetectionOne-stage Anchor-free Oriented Object DetectionOptical Character Recognition (OCR)