{"id":8719,"date":"2021-04-22T17:11:05","date_gmt":"2021-04-22T21:11:05","guid":{"rendered":"https:\/\/impresee.com\/?page_id=8719"},"modified":"2021-05-27T17:59:20","modified_gmt":"2021-05-27T21:59:20","slug":"scalable-visual-attribute-extraction","status":"publish","type":"page","link":"https:\/\/impresee.com\/es\/scalable-visual-attribute-extraction\/","title":{"rendered":"Scalable Visual Attribute Extraction through Hidden Layers of a Residual ConvNet"},"content":{"rendered":"

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Scalable Visual Attribute Extraction through Hidden Layers of a Residual ConvNet<\/h1>\n

[\/et_pb_text][et_pb_text _builder_version=”4.9.3″ _module_preset=”default” header_4_text_color=”#9cd333″]<\/p>\n

Andres Baloian
DCC University of Chile<\/span><\/h4>\n

abaloian@dcc.uchile.cl<\/span><\/p>\n


Nils Murrugarra-Llerena
Snap Research
<\/span><\/h4>\n

mnurrugarraller@snap.com<\/p>\n

<\/span><\/p>\n

Jose M. Saavedra
Impresee Inc.<\/span><\/h4>\n

\u00a0jose.saavedra@impresee.com<\/p>\n

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Abstract<\/h2>\n

Visual attributes play an essential role in real applications based on image retrieval. For instance, the extraction of attributes from images allows an eCommerce search engine to produce retrieval results with higher precision. The traditional manner to build an attribute extractor is by training a convnet-based classifier with a fixed number of classes. However, this approach does not scale for real applications where the number of attributes changes frequently. Therefore in this work, we propose an approach for extracting visual attributes from images, leveraging the learned capability of the hidden layers of a general convolutional network to discriminate among different visual features. We run experiments with a resnet-50 trained on Imagenet, on which we evaluate the output of its different blocks to discriminate between colors and textures. Our results show that the second block of the resnet is appropriate for discriminating colors, while the fourth block can be used for textures. In both cases, the achieved accuracy of attribute classification is superior to 93%. We also show that the proposed embeddings form local structures in the underlying feature space, which makes it possible to apply reduction techniques like UMAP, maintaining high accuracy and widely reducing the size of the feature space.<\/span><\/p>\n

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Scalable Visual Attribute Extraction through Hidden Layers of a Residual ConvNetAndres BaloianDCC University of Chile abaloian@dcc.uchile.cl Nils Murrugarra-LlerenaSnap Research mnurrugarraller@snap.com Jose M. SaavedraImpresee Inc. \u00a0jose.saavedra@impresee.comAbstract Visual attributes play an essential role in real applications based on image retrieval. For instance, the extraction of attributes from images allows an eCommerce search engine to produce retrieval results […]<\/p>","protected":false},"author":1,"featured_media":8728,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"","_et_gb_content_width":"","footnotes":""},"class_list":["post-8719","page","type-page","status-publish","has-post-thumbnail","hentry"],"yoast_head":"\nScalable Visual Attribute Extraction - Impresee eCommerce Labs<\/title>\n<meta name=\"description\" content=\"We propose an approach for extracting visual attributes from images, through the hidden layers of a general ResNet.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/impresee.com\/es\/scalable-visual-attribute-extraction\/\" \/>\n<meta property=\"og:locale\" content=\"es_ES\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Scalable Visual Attribute Extraction - Impresee eCommerce Labs\" \/>\n<meta property=\"og:description\" content=\"We propose an approach for extracting visual attributes from images, through the hidden layers of a general ResNet.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/impresee.com\/es\/scalable-visual-attribute-extraction\/\" \/>\n<meta property=\"og:site_name\" content=\"Impresee: Search bar and navigation solutions for eCommerce\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/impresee\/\" \/>\n<meta property=\"article:modified_time\" content=\"2021-05-27T21:59:20+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/impresee.com\/wp-content\/uploads\/umap_colores_bloque2.png\" \/>\n\t<meta property=\"og:image:width\" content=\"640\" \/>\n\t<meta property=\"og:image:height\" content=\"480\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:site\" content=\"@impresee\" \/>\n<meta name=\"twitter:label1\" content=\"Tiempo estimado de lectura\" \/>\n\t<meta name=\"twitter:data1\" content=\"4 minutos\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/impresee.com\/scalable-visual-attribute-extraction\/\",\"url\":\"https:\/\/impresee.com\/scalable-visual-attribute-extraction\/\",\"name\":\"Scalable Visual Attribute Extraction - Impresee eCommerce Labs\",\"isPartOf\":{\"@id\":\"https:\/\/impresee.com\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\/\/impresee.com\/scalable-visual-attribute-extraction\/#primaryimage\"},\"image\":{\"@id\":\"https:\/\/impresee.com\/scalable-visual-attribute-extraction\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/impresee.com\/wp-content\/uploads\/umap_colores_bloque2.png\",\"datePublished\":\"2021-04-22T21:11:05+00:00\",\"dateModified\":\"2021-05-27T21:59:20+00:00\",\"description\":\"We propose an approach for extracting visual attributes from images, through the hidden layers of a general ResNet.\",\"breadcrumb\":{\"@id\":\"https:\/\/impresee.com\/scalable-visual-attribute-extraction\/#breadcrumb\"},\"inLanguage\":\"es-CL\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/impresee.com\/scalable-visual-attribute-extraction\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"es-CL\",\"@id\":\"https:\/\/impresee.com\/scalable-visual-attribute-extraction\/#primaryimage\",\"url\":\"https:\/\/impresee.com\/wp-content\/uploads\/umap_colores_bloque2.png\",\"contentUrl\":\"https:\/\/impresee.com\/wp-content\/uploads\/umap_colores_bloque2.png\",\"width\":640,\"height\":480},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/impresee.com\/scalable-visual-attribute-extraction\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/impresee.com\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Scalable Visual Attribute Extraction through Hidden Layers of a Residual ConvNet\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/impresee.com\/#website\",\"url\":\"https:\/\/impresee.com\/\",\"name\":\"Impresee\",\"description\":\"AI search bar, filters and discount games for eCommerce to get more visitors, increase conversion and get repeat sales. 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