{"id":22,"date":"2025-05-09T21:25:52","date_gmt":"2025-05-09T21:25:52","guid":{"rendered":"https:\/\/mscvprojects.ri.cmu.edu\/2025team17\/?page_id=22"},"modified":"2025-12-12T18:55:03","modified_gmt":"2025-12-12T18:55:03","slug":"dataset","status":"publish","type":"page","link":"https:\/\/mscvprojects.ri.cmu.edu\/2025team17\/dataset\/","title":{"rendered":"Dataset"},"content":{"rendered":"\n<h2 class=\"wp-block-heading\"><a href=\"https:\/\/hd-epic.github.io\/\">HD-EPIC<\/a><\/h2>\n\n\n\n<p>The HD-EPIC dataset is an ego-centric long-video dataset focused on actions performed in the kitchen. It features long, in-the-wild recordings paired with dense annotations, including manually corrected narrations with precise action boundaries. In our project, since we focus on video question answering, we only use the video modality.<\/p>\n\n\n\n<p>HD-EPIC also provides a VQA benchmark built from its dense labels, covering seven question types: recipe, ingredient, nutrition, fine-grained action, 3D perception, object motion, and gaze. The benchmark is structured as 5-way multiple-choice QA, generated from 30 question prototypes for a total of 26,650 questions, with hard negatives sampled from the dataset to increase difficulty. <a href=\"https:\/\/hd-epic.github.io\/\" target=\"_blank\" rel=\"noreferrer noopener\"><\/a><\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"617\" src=\"https:\/\/mscvprojects.ri.cmu.edu\/2025team17\/wp-content\/uploads\/sites\/124\/2025\/12\/image-1-1024x617.png\" alt=\"\" class=\"wp-image-68\" srcset=\"https:\/\/mscvprojects.ri.cmu.edu\/2025team17\/wp-content\/uploads\/sites\/124\/2025\/12\/image-1-1024x617.png 1024w, https:\/\/mscvprojects.ri.cmu.edu\/2025team17\/wp-content\/uploads\/sites\/124\/2025\/12\/image-1-300x181.png 300w, https:\/\/mscvprojects.ri.cmu.edu\/2025team17\/wp-content\/uploads\/sites\/124\/2025\/12\/image-1-768x463.png 768w, https:\/\/mscvprojects.ri.cmu.edu\/2025team17\/wp-content\/uploads\/sites\/124\/2025\/12\/image-1-1536x926.png 1536w, https:\/\/mscvprojects.ri.cmu.edu\/2025team17\/wp-content\/uploads\/sites\/124\/2025\/12\/image-1.png 1612w\" sizes=\"auto, (max-width: 706px) 89vw, (max-width: 767px) 82vw, 740px\" \/><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\">References<\/h2>\n\n\n\n<p class=\"has-small-font-size\">[1] Perrett, T., et al. (2025). <em>HD-EPIC: A Highly-Detailed Egocentric Video Dataset<\/em>. arXiv2502.04144.<a href=\"https:\/\/arxiv.org\/abs\/2502.04144\"> https:\/\/arxiv.org\/abs\/2502.04144<\/a><\/p>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>HD-EPIC The HD-EPIC dataset is an ego-centric long-video dataset focused on actions performed in the kitchen. It features long, in-the-wild recordings paired with dense annotations, including manually corrected narrations with precise action boundaries. In our project, since we focus on video question answering, we only use the video modality. HD-EPIC also provides a VQA benchmark &hellip; <\/p>\n<p class=\"link-more\"><a href=\"https:\/\/mscvprojects.ri.cmu.edu\/2025team17\/dataset\/\" class=\"more-link\">Continue reading<span class=\"screen-reader-text\"> &#8220;Dataset&#8221;<\/span><\/a><\/p>\n","protected":false},"author":239,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-22","page","type-page","status-publish","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Dataset - Temporally Hierarchical Scene Graph Generation for Video Question Answering\u200b<\/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:\/\/mscvprojects.ri.cmu.edu\/2025team17\/dataset\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Dataset - Temporally Hierarchical Scene Graph Generation for Video Question Answering\u200b\" \/>\n<meta property=\"og:description\" content=\"HD-EPIC The HD-EPIC dataset is an ego-centric long-video dataset focused on actions performed in the kitchen. It features long, in-the-wild recordings paired with dense annotations, including manually corrected narrations with precise action boundaries. In our project, since we focus on video question answering, we only use the video modality. HD-EPIC also provides a VQA benchmark &hellip; Continue reading &quot;Dataset&quot;\" \/>\n<meta property=\"og:url\" content=\"https:\/\/mscvprojects.ri.cmu.edu\/2025team17\/dataset\/\" \/>\n<meta property=\"og:site_name\" content=\"Temporally Hierarchical Scene Graph Generation for Video Question Answering\u200b\" \/>\n<meta property=\"article:modified_time\" content=\"2025-12-12T18:55:03+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/mscvprojects.ri.cmu.edu\/2025team17\/wp-content\/uploads\/sites\/124\/2025\/12\/image-1.png\" \/>\n\t<meta property=\"og:image:width\" content=\"1612\" \/>\n\t<meta property=\"og:image:height\" content=\"972\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"1 minute\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/mscvprojects.ri.cmu.edu\\\/2025team17\\\/dataset\\\/\",\"url\":\"https:\\\/\\\/mscvprojects.ri.cmu.edu\\\/2025team17\\\/dataset\\\/\",\"name\":\"Dataset - Temporally Hierarchical Scene Graph Generation for Video Question Answering\u200b\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/mscvprojects.ri.cmu.edu\\\/2025team17\\\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\\\/\\\/mscvprojects.ri.cmu.edu\\\/2025team17\\\/dataset\\\/#primaryimage\"},\"image\":{\"@id\":\"https:\\\/\\\/mscvprojects.ri.cmu.edu\\\/2025team17\\\/dataset\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/mscvprojects.ri.cmu.edu\\\/2025team17\\\/wp-content\\\/uploads\\\/sites\\\/124\\\/2025\\\/12\\\/image-1-1024x617.png\",\"datePublished\":\"2025-05-09T21:25:52+00:00\",\"dateModified\":\"2025-12-12T18:55:03+00:00\",\"breadcrumb\":{\"@id\":\"https:\\\/\\\/mscvprojects.ri.cmu.edu\\\/2025team17\\\/dataset\\\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\\\/\\\/mscvprojects.ri.cmu.edu\\\/2025team17\\\/dataset\\\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\\\/\\\/mscvprojects.ri.cmu.edu\\\/2025team17\\\/dataset\\\/#primaryimage\",\"url\":\"https:\\\/\\\/mscvprojects.ri.cmu.edu\\\/2025team17\\\/wp-content\\\/uploads\\\/sites\\\/124\\\/2025\\\/12\\\/image-1.png\",\"contentUrl\":\"https:\\\/\\\/mscvprojects.ri.cmu.edu\\\/2025team17\\\/wp-content\\\/uploads\\\/sites\\\/124\\\/2025\\\/12\\\/image-1.png\",\"width\":1612,\"height\":972},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\\\/\\\/mscvprojects.ri.cmu.edu\\\/2025team17\\\/dataset\\\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\\\/\\\/mscvprojects.ri.cmu.edu\\\/2025team17\\\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Dataset\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\\\/\\\/mscvprojects.ri.cmu.edu\\\/2025team17\\\/#website\",\"url\":\"https:\\\/\\\/mscvprojects.ri.cmu.edu\\\/2025team17\\\/\",\"name\":\"Temporally Hierarchical Scene Graph Generation for Video Question Answering\u200b\",\"description\":\"\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\\\/\\\/mscvprojects.ri.cmu.edu\\\/2025team17\\\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Dataset - Temporally Hierarchical Scene Graph Generation for Video Question Answering\u200b","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/mscvprojects.ri.cmu.edu\/2025team17\/dataset\/","og_locale":"en_US","og_type":"article","og_title":"Dataset - Temporally Hierarchical Scene Graph Generation for Video Question Answering\u200b","og_description":"HD-EPIC The HD-EPIC dataset is an ego-centric long-video dataset focused on actions performed in the kitchen. 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