{"id":3387,"date":"2020-08-13T10:56:28","date_gmt":"2020-08-13T09:56:28","guid":{"rendered":"http:\/\/www.ceessnoek.info\/?p=3387"},"modified":"2020-08-13T10:56:44","modified_gmt":"2020-08-13T09:56:44","slug":"bmvc-bias-awareness-for-zero-shot-learning-the-seen-and-unseen","status":"publish","type":"post","link":"https:\/\/www.ceessnoek.info\/index.php\/bmvc-bias-awareness-for-zero-shot-learning-the-seen-and-unseen\/","title":{"rendered":"BMVC: Bias-Awareness for Zero-Shot Learning the Seen and Unseen"},"content":{"rendered":"\n<p>The BMVC 2020 paper <em>Bias-Awareness for Zero-Shot Learning the Seen and Unseen <\/em>by <a href=\"https:\/\/staff.fnwi.uva.nl\/w.e.thong\/\">William Thong<\/a> and Cees Snoek is <a href=\"http:\/\/isis-data.science.uva.nl\/cgmsnoek\/pub\/thong-bias-bmvc2020.pdf\">now available<\/a>. Generalized zero-shot learning recognizes inputs from both seen and unseen classes. Yet, existing methods tend to be biased towards the classes seen during training. In this paper, we strive to mitigate this bias. We propose a bias-aware learner to map inputs to a semantic embedding space for generalized zero-shot learning. During training, the model learns to regress to real-valued class prototypes in the embedding space with temperature scaling, while a margin-based bidirectional entropy term regularizes seen and unseen probabilities. Relying on a real-valued semantic embedding space provides a versatile approach, as the model can operate on different types of semantic information for both seen and unseen classes. Experiments are carried out on four benchmarks for generalized zero-shot learning and demonstrate the benefits of the proposed bias-aware classifier, both as a stand-alone method or in combination with generated features.<\/p>\n\n\n\n<figure class=\"wp-block-image\"><img loading=\"lazy\" decoding=\"async\" width=\"1014\" height=\"716\" src=\"http:\/\/www.ceessnoek.info\/wp-content\/uploads\/2020\/08\/thong-bias.png\" alt=\"\" class=\"wp-image-3388\" srcset=\"https:\/\/www.ceessnoek.info\/wp-content\/uploads\/2020\/08\/thong-bias.png 1014w, https:\/\/www.ceessnoek.info\/wp-content\/uploads\/2020\/08\/thong-bias-300x212.png 300w, https:\/\/www.ceessnoek.info\/wp-content\/uploads\/2020\/08\/thong-bias-768x542.png 768w\" sizes=\"auto, (max-width: 1014px) 100vw, 1014px\" \/><\/figure>\n","protected":false},"excerpt":{"rendered":"<p>The BMVC 2020 paper Bias-Awareness for Zero-Shot Learning the Seen and Unseen by William Thong and Cees Snoek is now available. Generalized zero-shot learning recognizes inputs from both seen and unseen classes. Yet, existing methods tend to be biased towards the classes seen during training. In this paper, we strive to mitigate this bias. We [&hellip;]<\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[4,1],"tags":[],"class_list":["post-3387","post","type-post","status-publish","format-standard","hentry","category-science","category-uncategorized"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.3 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>BMVC: Bias-Awareness for Zero-Shot Learning the Seen and Unseen - Cees Snoek<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.ceessnoek.info\/index.php\/bmvc-bias-awareness-for-zero-shot-learning-the-seen-and-unseen\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"BMVC: Bias-Awareness for Zero-Shot Learning the Seen and Unseen - Cees Snoek\" \/>\n<meta property=\"og:description\" content=\"The BMVC 2020 paper Bias-Awareness for Zero-Shot Learning the Seen and Unseen by William Thong and Cees Snoek is now available. Generalized zero-shot learning recognizes inputs from both seen and unseen classes. Yet, existing methods tend to be biased towards the classes seen during training. In this paper, we strive to mitigate this bias. We [&hellip;]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.ceessnoek.info\/index.php\/bmvc-bias-awareness-for-zero-shot-learning-the-seen-and-unseen\/\" \/>\n<meta property=\"og:site_name\" content=\"Cees Snoek\" \/>\n<meta property=\"article:published_time\" content=\"2020-08-13T09:56:28+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2020-08-13T09:56:44+00:00\" \/>\n<meta property=\"og:image\" content=\"http:\/\/www.ceessnoek.info\/wp-content\/uploads\/2020\/08\/thong-bias.png\" \/>\n<meta name=\"author\" content=\"Cees\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Cees\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"1 minute\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.ceessnoek.info\/index.php\/bmvc-bias-awareness-for-zero-shot-learning-the-seen-and-unseen\/\",\"url\":\"https:\/\/www.ceessnoek.info\/index.php\/bmvc-bias-awareness-for-zero-shot-learning-the-seen-and-unseen\/\",\"name\":\"BMVC: Bias-Awareness for Zero-Shot Learning the Seen and Unseen - 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