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index.html
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<!doctype html>
<html lang="en">
<head>
<!-- Required meta tags -->
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
<!-- Bootstrap CSS -->
<link rel="stylesheet" href="https://stackpath.bootstrapcdn.com/bootstrap/4.4.1/css/bootstrap.min.css"
integrity="sha384-Vkoo8x4CGsO3+Hhxv8T/Q5PaXtkKtu6ug5TOeNV6gBiFeWPGFN9MuhOf23Q9Ifjh" crossorigin="anonymous">
<link rel="stylesheet" href="main.css">
<title>Large scale product recognition dataset</title>
</head>
<body>
<nav class="navbar navbar-expand-lg navbar-light bg-light" id="nav">
<div class="container"><a href="#" class="navbar-brand">Products-10K</a>
<ul class="navbar-nav mr-auto order-1">
<li class="nav-item"><a class="nav-link" href="#overview">Overview</a></li>
<li class="nav-item"><a class="nav-link" href="#dates">Important Dates</a></li>
<li class="nav-item"><a class="nav-link" href="#paper">Paper</a></li>
<li class="nav-item"><a class="nav-link" href="./challenge.html" target="_blank">Challenge</a></li>
</ul>
</div>
</div>
</nav>
<main id="main" class="site-main main">
<section class="container" id="banner">
<img src="./img/products-10k-logo-2.png" width=120>
<div class="title-text-box">
<h1 class="display-4 text-bold">Products-10K</h1>
<h2 class="display-5 text-bold">Large Scale Product Recognition Dataset</h1>
<h5 class="text-regular">JD AI research</h5>
</div>
<a class="btn" id="learn-more-btn" href="#overview" role="button">Learn more</a>
<a class="btn" id="download-btn" href="./challenge.html" role="button" target="_blank">Download dataset</a>
</section>
<section class="container">
<div class="card" id="overview">
<div class="card-body">
<div class="media">
<embed src="./img/dataset.svg" type="image/svg+xml" class="mr-3 align-self-center" width=40/>
<div class="media-body">
<h5 class="mt-0">Overview</h5>
Products-10k: Large Scale Product Recognition Dataset
</div>
</div>
<p class="card-text">With the rapid development of electronic commerce, the way of shopping has
experienced a revolutionary evolution. To fully meet customers’ massive and diverse online
shopping needs with quick response, retailing AI system needs to automatically recognize
products from images and videos at the stock-keeping unit (SKU) level with high accuracy.
However, product recognition is still a challenging task, since many of SKU-level products are
fine-grained and visually similar by a rough glimpse. Although there are already some products
benchmarks available, these datasets are either too small (limited number of products) or
noisy-labeled (lack of human labeling).
</p>
<p class="card-text">
We construct a human-labeled products image dataset named “Products-10k”, which is so far the
largest production recognition dataset containing 10,000 products frequently bought by online
customers in JD.com, covering a full spectrum of categories including Fashion, 3C, food,
healthcare, household commodities, etc.. Moreover, large-scale product labels are organized as a
graph to indicate the complex hierarchy and inter-dependency among products.
</p>
<p class="card-text">
Based on this dataset, we organize the 1st Challenge on SKU-level production recognition. The
final results will be announced at ICPR2020, and the winner will be invited to present their
approaches at the workshop. We encourage engineers and researchers from the pattern recognition
community to develop novel algorithms for this practical and challenging task.
</p>
</div>
</div>
<div class="card" id="dates">
<div class="card-body">
<div class="media">
<embed src="./img/calender.svg" type="image/svg+xml" class="mr-3 align-self-center" width=40/>
<div class="media-body">
<h5 class="mt-0">Important Dates</h5>
Important dates of Large scale Product Recognition Challenge
</div>
</div>
<p class="card-text">
Due to the difficulties imposed by the global coronavirus epidemic, we decided to delay the Challenge Lauch Date from May to August this year.
</p>
<p class="card-text">
Competition URL <a href="https://www.kaggle.com/c/products-10k">https://www.kaggle.com/c/products-10k</a>
</p>
<table class="table table-striped table-bordered">
<tbody>
<tr>
<td>Challenge Launch Data</td>
<td>August 20, 2020</td>
</tr>
<tr>
<td>Challenge Submissions deadline</td>
<td>Sepetember 30, 2020</td>
</tr>
<tr>
<td>Challenge Award Notification</td>
<td>October 7, 2020</td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="card" id="paper">
<div class="card-body">
<div class="media">
<embed src="./img/icon-paper.svg" type="image/svg+xml" class="mr-3 align-self-center" width=40/>
<div class="media-body">
<h5 class="mt-0">Paper</h5>
Paper for Products-10k
</div>
</div>
<p class="card-text">Please cite the following paper if you use our dataset.</p>
<p class="card-text">Yalong Bai, Yuxiang Chen, Wei Yu, Linfang Wang, Wei Zhang. "Products-10K: A Large-scale Product Recognition Dataset". [<a href="https://arxiv.org/abs/2008.10545">arXiv</a>]</p>
</div>
</div>
</section>
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<p class="footer-text">JDAI Research</p>
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