{"url":"/dataset/didemo","name":"DiDeMo","full_name":"Distinct Describable Moments","description_markdown":"The **Distinct Describable Moments** (**DiDeMo**) dataset is one of the largest and most diverse datasets for the temporal localization of events in videos given natural language descriptions. The videos are collected from Flickr and each video is trimmed to a maximum of 30 seconds. The videos in the dataset are divided into 5-second segments to reduce the complexity of annotation. The dataset is split into training, validation and test sets containing 8,395, 1,065 and 1,004 videos respectively. The dataset contains a total of 26,892 moments and one moment could be associated with descriptions from multiple annotators. The descriptions in DiDeMo dataset are detailed and contain camera movement, temporal transition indicators, and activities. 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nothing here re-ranks them"},{"leaderboard":"/sota/zero-shot-video-retrieval-on-didemo","task":"Zero-Shot Video Retrieval","dataset_variant":"DiDeMo","rows":26,"metrics":["text-to-video R@1","text-to-video R@5","text-to-video R@10","video-to-text R@1","video-to-text R@5","video-to-text R@10","text-to-video Median Rank","video-to-text Median Rank"],"first_row_in_archive_order":{"model":"InternVideo2-6B","paper":"/paper/internvideo2-scaling-video-foundation-models","metrics":{"text-to-video R@1":"57.9","text-to-video R@10":"84.6","text-to-video R@5":"80.0","video-to-text R@1":"57.1","video-to-text R@10":"85.0","video-to-text R@5":"79.9"},"code_links":[{"title":"opengvlab/internvideo","url":"https://github.com/opengvlab/internvideo"},{"title":"opengvlab/internvideo2","url":"https://github.com/opengvlab/internvideo2"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/natural-language-moment-retrieval-on-didemo","task":"Natural Language Moment Retrieval","dataset_variant":"DiDeMo","rows":1,"metrics":["R@1,IoU=0.5","R@1,IoU=0.7","R@1,IoU=1.0","R@5,IoU=0.5","R@5,IoU=0.7","R@5,IoU=1.0"],"first_row_in_archive_order":{"model":"VLG-Net","paper":"/paper/vlg-net-video-language-graph-matching-network","metrics":{"R@1,IoU=0.5":"33.35","R@1,IoU=0.7":"25.57","R@1,IoU=1.0":"25.57","R@5,IoU=0.5":"88.86","R@5,IoU=0.7":"71.72","R@5,IoU=1.0":"71.65"},"code_links":[{"title":"Soldelli/VLG-Net","url":"https://github.com/Soldelli/VLG-Net"}]},"note":"rows are the archive's own order at snapshot; 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