{"id":60,"date":"2024-09-09T11:01:30","date_gmt":"2024-09-09T18:01:30","guid":{"rendered":"https:\/\/labs.engineering.asu.edu\/rftest\/?page_id=60"},"modified":"2024-09-25T12:04:11","modified_gmt":"2024-09-25T19:04:11","slug":"machine-learning-datasets","status":"publish","type":"page","link":"https:\/\/labs.engineering.asu.edu\/rftest\/machine-learning-datasets\/","title":{"rendered":"AI Datasets"},"content":{"rendered":"\n<div class=\"wp-block-group is-nowrap is-layout-flex wp-container-core-group-is-layout-6c531013 wp-block-group-is-layout-flex\">\n<p class=\"has-text-align-left\" style=\"margin-right:0;margin-left:0\"><strong>HazyTrack Dataset <\/strong><br>This synthetic dataset is created for measuring the effect of dehazing algorithms on visual object tracking task. Each scenario folder contains synthetically generated hazy and reference scenes. Each folder has a ground truth file for the object bounding box positions that can be used for initializing and evaluating object tracking algorithms.<br><br><a href=\"https:\/\/drive.google.com\/file\/d\/1rEywJc3KtpRvHm6TWg9eBLudg1Hhyq_v\/view?usp=sharing\">Download Dataset<\/a><br><br>Please cite the following paper if you would like to use this dataset.<br>H. Seckin Demir, Noah Rajbharti, Sloan Sciarappo, Jennifer Blain Christen, and Sule Ozev, &#8220;Evaluating the Impact of Dehazing Algorithms on Visual Object Tracking Performance&#8221;, In Proceedings of the International Symposium on Visual Computing (ISVC), Lake Tahoe, NV, USA, 21\u201323 October 2024; Springer<\/p>\n\n\n\n<p class=\"has-text-align-left\"><img loading=\"lazy\" decoding=\"async\" width=\"1000\" height=\"735\" class=\"wp-image-86\" style=\"width: 1000px;\" src=\"https:\/\/labs.engineering.asu.edu\/rftest\/wp-content\/uploads\/sites\/208\/2024\/09\/unity.png\" alt=\"\" srcset=\"https:\/\/labs.engineering.asu.edu\/rftest\/wp-content\/uploads\/sites\/208\/2024\/09\/unity.png 1367w, https:\/\/labs.engineering.asu.edu\/rftest\/wp-content\/uploads\/sites\/208\/2024\/09\/unity-500x368.png 500w, https:\/\/labs.engineering.asu.edu\/rftest\/wp-content\/uploads\/sites\/208\/2024\/09\/unity-1000x735.png 1000w\" sizes=\"auto, (max-width: 1367px) 100vw, 1367px\" \/><\/p>\n<\/div>\n\n\n\n<p class=\"has-text-align-right\"><\/p>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p class=\"mb-2\">HazyTrack Dataset This synthetic dataset is created for measuring the effect of dehazing algorithms on visual object tracking task. Each scenario folder contains synthetically generated hazy and reference scenes. Each folder has a ground truth file for the object bounding box positions that can be used for initializing and evaluating object tracking algorithms. Download Dataset&#8230;<\/p>\n","protected":false},"author":392,"featured_media":0,"parent":0,"menu_order":5,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"footnotes":""},"class_list":["post-60","page","type-page","status-publish","hentry"],"acf":[],"_links":{"self":[{"href":"https:\/\/labs.engineering.asu.edu\/rftest\/wp-json\/wp\/v2\/pages\/60","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/labs.engineering.asu.edu\/rftest\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/labs.engineering.asu.edu\/rftest\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/labs.engineering.asu.edu\/rftest\/wp-json\/wp\/v2\/users\/392"}],"replies":[{"embeddable":true,"href":"https:\/\/labs.engineering.asu.edu\/rftest\/wp-json\/wp\/v2\/comments?post=60"}],"version-history":[{"count":0,"href":"https:\/\/labs.engineering.asu.edu\/rftest\/wp-json\/wp\/v2\/pages\/60\/revisions"}],"wp:attachment":[{"href":"https:\/\/labs.engineering.asu.edu\/rftest\/wp-json\/wp\/v2\/media?parent=60"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}