{"url":"/dataset/conferencevideosegmentationdataset","name":"ConferenceVideoSegmentationDataset","full_name":null,"description_markdown":"This is a video and image segmentation dataset for human head and shoulders, relevant for creating elegant media for videoconferencing and virtual reality applications. The source\r\ndata includes ten online conference-style green screen videos. The authors extracted 3600 frames from the videos and generated the ground truth masks for each character in the video, and then applied virtual background to the frames to generate the training/testing sets.","description_withheld":null,"homepage":"https://github.com/kuangzijian/Flow-Based-Video-Matting","introduced_date":"2021-04-20","introduced_date_note":null,"introduced_by":{"paper":"/paper/flow-based-video-segmentation-for-human-head","title":"Flow-based Video Segmentation for Human Head and Shoulders","first_author":"Zijian Kuang","url":null},"license":{"name":"Unknown","url":null},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Videos","url":"/datasets/modality/videos"}],"tasks":[{"name":"Video Segmentation","url":"/task/video-segmentation","datasets_with_task":"/datasets/task/video-segmentation"}],"languages":[],"variants":["ConferenceVideoSegmentationDataset"],"data_loaders":[{"repo":"https://github.com/kuangzijian/Flow-Based-Video-Matting","url":"https://github.com/kuangzijian/Flow-Based-Video-Matting","frameworks":["pytorch"]}],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}