{"id":1461,"date":"2026-07-03T13:57:41","date_gmt":"2026-07-03T13:57:41","guid":{"rendered":"https:\/\/cv.inf.elte.hu\/?p=1461"},"modified":"2026-07-03T14:20:42","modified_gmt":"2026-07-03T14:20:42","slug":"icra-2026-new-paper-on-real-time-surface-normal-estimation","status":"publish","type":"post","link":"https:\/\/cv.inf.elte.hu\/index.php\/2026\/07\/03\/icra-2026-new-paper-on-real-time-surface-normal-estimation\/","title":{"rendered":"ICRA 2026: New Paper on Real-Time Surface Normal Estimation"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\">We are thrilled to announce that our latest research, &#8220;Robust and Real-time Surface Normal Estimation from Stereo Disparities using Affine Transformations&#8221;<sup><\/sup>, was successfully presented at the prestigious ICRA 2026 conference in Vienna. Our colleague, Levente Hajder, showcased the poster detailing this collaborative work, authored alongside Csongor Csan\u00e1d Karik\u00f3 and Muhammad Rafi Faisal from the Geometric Computer Vision Group at E\u00f6tv\u00f6s Lor\u00e1nd University<sup><\/sup>. The paper addresses a crucial challenge in computer vision and robotics: the rapid and accurate generation of oriented point clouds<sup><\/sup><sup><\/sup><sup><\/sup><sup><\/sup>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">he novel method introduced by our team leverages affine transformations derived directly from disparity values in rectified stereo image pairs, a technique that significantly reduces computational complexity. To ensure both high speed and robustness against noise, the approach utilizes a custom algorithm inspired by convolutional operations , paired with adaptive heuristic techniques to efficiently detect connected surface components. Validated on the Middlebury and Cityscapes datasets, this purely geometric, GPU-powered solution achieves real-time performance and significantly outperforms traditional PCA-based normal estimation methods in both speed and accuracy.<br><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><a href=\"https:\/\/arxiv.org\/abs\/2504.15121\">Arxiv paper available.<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n\n<figure class=\"wp-block-image size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"824\" height=\"396\" src=\"https:\/\/cv.inf.elte.hu\/wp-content\/uploads\/2026\/07\/image.png\" alt=\"\" class=\"wp-image-1464\" style=\"width:477px;height:auto\" srcset=\"https:\/\/cv.inf.elte.hu\/wp-content\/uploads\/2026\/07\/image.png 824w, https:\/\/cv.inf.elte.hu\/wp-content\/uploads\/2026\/07\/image-300x144.png 300w, https:\/\/cv.inf.elte.hu\/wp-content\/uploads\/2026\/07\/image-768x369.png 768w\" sizes=\"auto, (max-width: 824px) 100vw, 824px\" \/><\/figure>\n","protected":false},"excerpt":{"rendered":"<p>We are thrilled to announce that our latest research, &#8220;Robust and Real-time Surface Normal Estimation from Stereo Disparities using Affine Transformations&#8221;, was successfully presented at the prestigious ICRA 2026 conference in Vienna. Our colleague, Levente Hajder, showcased the poster detailing this collaborative work, authored alongside Csongor Csan\u00e1d Karik\u00f3 and Muhammad Rafi Faisal from the Geometric [&hellip;]<\/p>\n","protected":false},"author":4,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"post_folder":[],"class_list":["post-1461","post","type-post","status-publish","format-standard","hentry","category-egyeb"],"_links":{"self":[{"href":"https:\/\/cv.inf.elte.hu\/index.php\/wp-json\/wp\/v2\/posts\/1461","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/cv.inf.elte.hu\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/cv.inf.elte.hu\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/cv.inf.elte.hu\/index.php\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/cv.inf.elte.hu\/index.php\/wp-json\/wp\/v2\/comments?post=1461"}],"version-history":[{"count":3,"href":"https:\/\/cv.inf.elte.hu\/index.php\/wp-json\/wp\/v2\/posts\/1461\/revisions"}],"predecessor-version":[{"id":1467,"href":"https:\/\/cv.inf.elte.hu\/index.php\/wp-json\/wp\/v2\/posts\/1461\/revisions\/1467"}],"wp:attachment":[{"href":"https:\/\/cv.inf.elte.hu\/index.php\/wp-json\/wp\/v2\/media?parent=1461"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/cv.inf.elte.hu\/index.php\/wp-json\/wp\/v2\/categories?post=1461"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/cv.inf.elte.hu\/index.php\/wp-json\/wp\/v2\/tags?post=1461"},{"taxonomy":"post_folder","embeddable":true,"href":"https:\/\/cv.inf.elte.hu\/index.php\/wp-json\/wp\/v2\/post_folder?post=1461"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}