{"id":1529,"date":"2026-02-26T20:42:19","date_gmt":"2026-02-26T20:42:19","guid":{"rendered":"https:\/\/synasc.ro\/2026\/?page_id=1529"},"modified":"2026-04-01T11:16:36","modified_gmt":"2026-04-01T11:16:36","slug":"nicu-sebe","status":"publish","type":"page","link":"https:\/\/synasc.ro\/2026\/invited-speakers\/nicu-sebe\/","title":{"rendered":"Nicu Sebe"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-page\" data-elementor-id=\"1529\" class=\"elementor elementor-1529\" data-elementor-post-type=\"page\">\n\t\t\t\t<div class=\"elementor-element elementor-element-3e0b8ee e-con-full e-flex e-con e-parent\" data-id=\"3e0b8ee\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-a3ba736 elementor-widget elementor-widget-heading\" data-id=\"a3ba736\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">How AI Learns to See, Generate, and Judge Fairly<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-80ba9f5 elementor-widget elementor-widget-heading\" data-id=\"80ba9f5\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Nicu Sebe<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7088b6b elementor-widget elementor-widget-text-editor\" data-id=\"7088b6b\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p>University of Trento, Italy<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-6af37d1 elementor-widget elementor-widget-image\" data-id=\"6af37d1\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img fetchpriority=\"high\" decoding=\"async\" width=\"231\" height=\"300\" src=\"https:\/\/synasc.ro\/2026\/wp-content\/uploads\/sites\/28\/2026\/04\/Nicu3-1-231x300.jpg\" class=\"attachment-medium size-medium wp-image-1547\" alt=\"\" srcset=\"https:\/\/synasc.ro\/2026\/wp-content\/uploads\/sites\/28\/2026\/04\/Nicu3-1-231x300.jpg 231w, https:\/\/synasc.ro\/2026\/wp-content\/uploads\/sites\/28\/2026\/04\/Nicu3-1-787x1024.jpg 787w, https:\/\/synasc.ro\/2026\/wp-content\/uploads\/sites\/28\/2026\/04\/Nicu3-1-768x999.jpg 768w, https:\/\/synasc.ro\/2026\/wp-content\/uploads\/sites\/28\/2026\/04\/Nicu3-1-1180x1536.jpg 1180w, https:\/\/synasc.ro\/2026\/wp-content\/uploads\/sites\/28\/2026\/04\/Nicu3-1-1574x2048.jpg 1574w, https:\/\/synasc.ro\/2026\/wp-content\/uploads\/sites\/28\/2026\/04\/Nicu3-1-scaled.jpg 1967w\" sizes=\"(max-width: 231px) 100vw, 231px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-6e257af elementor-align-center elementor-hidden-widescreen elementor-hidden-desktop elementor-hidden-tablet elementor-hidden-mobile elementor-icon-list--layout-traditional elementor-list-item-link-full_width elementor-widget elementor-widget-icon-list\" data-id=\"6e257af\" data-element_type=\"widget\" data-widget_type=\"icon-list.default\">\n\t\t\t\t\t\t\t<ul class=\"elementor-icon-list-items\">\n\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<a href=\"#\">\n\n\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-globe\" viewBox=\"0 0 496 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M336.5 160C322 70.7 287.8 8 248 8s-74 62.7-88.5 152h177zM152 256c0 22.2 1.2 43.5 3.3 64h185.3c2.1-20.5 3.3-41.8 3.3-64s-1.2-43.5-3.3-64H155.3c-2.1 20.5-3.3 41.8-3.3 64zm324.7-96c-28.6-67.9-86.5-120.4-158-141.6 24.4 33.8 41.2 84.7 50 141.6h108zM177.2 18.4C105.8 39.6 47.8 92.1 19.3 160h108c8.7-56.9 25.5-107.8 49.9-141.6zM487.4 192H372.7c2.1 21 3.3 42.5 3.3 64s-1.2 43-3.3 64h114.6c5.5-20.5 8.6-41.8 8.6-64s-3.1-43.5-8.5-64zM120 256c0-21.5 1.2-43 3.3-64H8.6C3.2 212.5 0 233.8 0 256s3.2 43.5 8.6 64h114.6c-2-21-3.2-42.5-3.2-64zm39.5 96c14.5 89.3 48.7 152 88.5 152s74-62.7 88.5-152h-177zm159.3 141.6c71.4-21.2 129.4-73.7 158-141.6h-108c-8.8 56.9-25.6 107.8-50 141.6zM19.3 352c28.6 67.9 86.5 120.4 158 141.6-24.4-33.8-41.2-84.7-50-141.6h-108z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Webpage<\/span>\n\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-89d48db elementor-widget elementor-widget-heading\" data-id=\"89d48db\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">ABSTRACT<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-dd1252a elementor-widget elementor-widget-text-editor\" data-id=\"dd1252a\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p>In the first part of the lecture, I will explore how we teach AI to generate videos without relying on detailed annotations or object specific labels. By training on collections of similar videos \u2013 such as faces or human bodies \u2013 the model learns to generalize across an entire category. Building on this idea, we developed a Learnable Game Engine (LGE) that learns from simple monocular videos to keep track of scenes and objects and to re render them from different viewpoints. Much like a real game engine, it captures basic physics and logic, allowing users to control the scene or guide virtual agents through high level language instructions. The second part of the lecture turns to the safety and fairness of generative AI. Most existing approaches look only for predefined types of bias, but real world systems can exhibit unexpected ones. To address this, we introduce OpenBias, a method that uncovers and measures previously unknown biases in text to image models without relying on any preset list. Our experiments show that OpenBias aligns well with established methods and with human judgment, offering a more flexible way to assess fairness in generative systems.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8c706e9 elementor-widget elementor-widget-heading\" data-id=\"8c706e9\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">SHORT BIO<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-0b87dae elementor-widget elementor-widget-text-editor\" data-id=\"0b87dae\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p>Nicu Sebe is a professor in the University of Trento, Italy, where he is leading the research in the areas of multimedia information retrieval and human-computer interaction in computer vision applications. He received his PhD from the University of Leiden, The Netherlands and has been in the past with the University of Amsterdam, The Netherlands and the University of Illinois at Urbana-Champaign, USA. He was involved in the organization of the major conferences and workshops addressing the computer vision and human-centered aspects of multimedia information retrieval, among which as a General Co-Chair of the IEEE Automatic Face and Gesture Recognition Conference, FG 2008, ACM International Conference on Multimedia Retrieval (ICMR) 2017 and ACM Multimedia 2013. He was a program chair of ACM Multimedia 2011 and 2007, ECCV 2016, ICCV 2017, ICPR 2020 and a general chair of ACM Multimedia 2022. He was a program chair of CVPR 2027 and a General Chair of ACM Multimedia 2027 and ECCV 2028. He is the Co-Editor in Chief of the Computer Vision and Image Understanding journal. He is a fellow of ELLIS, IAPR and a Senior member of ACM and IEEE.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>How AI Learns to See, Generate, and Judge Fairly Nicu Sebe University of Trento, Italy Webpage ABSTRACT In the first part of the lecture, I will explore how we teach AI to generate videos without relying on detailed annotations or object specific labels. By training on collections of similar videos \u2013 such as faces or [&hellip;]<\/p>\n","protected":false},"author":30,"featured_media":0,"parent":226,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-1529","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/synasc.ro\/2026\/wp-json\/wp\/v2\/pages\/1529","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/synasc.ro\/2026\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/synasc.ro\/2026\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/synasc.ro\/2026\/wp-json\/wp\/v2\/users\/30"}],"replies":[{"embeddable":true,"href":"https:\/\/synasc.ro\/2026\/wp-json\/wp\/v2\/comments?post=1529"}],"version-history":[{"count":13,"href":"https:\/\/synasc.ro\/2026\/wp-json\/wp\/v2\/pages\/1529\/revisions"}],"predecessor-version":[{"id":1557,"href":"https:\/\/synasc.ro\/2026\/wp-json\/wp\/v2\/pages\/1529\/revisions\/1557"}],"up":[{"embeddable":true,"href":"https:\/\/synasc.ro\/2026\/wp-json\/wp\/v2\/pages\/226"}],"wp:attachment":[{"href":"https:\/\/synasc.ro\/2026\/wp-json\/wp\/v2\/media?parent=1529"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}