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authoradamhrv <adam@ahprojects.com>2019-05-02 19:57:21 +0200
committeradamhrv <adam@ahprojects.com>2019-05-02 19:57:21 +0200
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+------------
+
+status: draft
+title: IBM Diversity in Faces
+desc: <span class="dataset-name">IBM Diversity in Faces</span> is a person re-identification dataset of images captured at UC Santa Cruz in 2007
+subdesc: IBM Diversity in Faces contains 1,264 images and 632 persons on the UC Santa Cruz campus and is used to train person re-identification algorithms for surveillance
+slug: IBM Diversity in Faces
+cssclass: dataset
+image: assets/background.jpg
+year: 2007
+published: 2019-2-23
+updated: 2019-2-23
+authors: Adam Harvey
+
+------------
+
+## IBM Diversity in Faces Dataset
+
+### sidebar
+### end sidebar
+
+[ page under development ]
+
+in "Understanding Unequal Gender Classification Accuracyfrom Face Images" researcher affilliated with IBM created a new version of PPB so they didn't have to agree to the terms of the original PPB.
+
+>We use an approximation of the PPB dataset for the ex-periments in this paper. This dataset contains images ofparliament members from the six countries identified in[4] and were manually labeled by us into the categoriesdark-skinned and light-skinned.1Our approximation tothe PPB dataset, which we call PPB*, is very similar toPPB and satisfies the relevant characteristics for the study we perform. Table 1 compares the decomposition of theoriginal PPB dataset and our PPB* approximation accord-ing to skin type and gender.
+
+{% include 'dashboard.html' %} \ No newline at end of file