{"url":"/dataset/omnilab","name":"OmniLab","full_name":null,"description_markdown":"In order to evaluate the effectiveness of NToP in real-world scenarios, we collect a new dataset OmniLab with a top-view omnidirectional camera, mounted on the ceiling of two different rooms (bedroom, living room) at 2.5 m height. Five actors (3 males, 2 females) perform 15 actions from CMU-MoCap database (brooming, cleaning windows, down and get up, drinking, fall-on-face, in chair and stand up, pull object, push object, rugpull, turn left, turn right, upbend from knees, upbend from waist, up from ground, walk, walk-old-man) in two rooms with varying clothes. The recorded action length is 2.5 s, which results in 60 images for each scene at a frame rate of 24 FPS. The position of the camera is fixed and the resolution of the images is 1200 by 1200 pixels. A total of 4800 frames are collected. All annotations of 17 keypoints conforming to COCO conventions are estimated through a keypoint detector and subsequently refined by four different humans in two loops to ensure high annotation quality. Bottom figure shows a few examples from OmniLab with person bounding boxes and keypoint annotations.","description_withheld":null,"homepage":"https://www.tu-chemnitz.de/etit/dst/forschung/comp_vision/datasets/omnilab/","introduced_date":"2024-02-28","introduced_date_note":null,"introduced_by":{"paper":"/paper/ntop-nerf-powered-large-scale-dataset","title":"NToP: NeRF-Powered Large-scale Dataset Generation for 2D and 3D Human Pose Estimation in Top-View Fisheye Images","first_author":"Jingrui Yu","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Actions","url":"/datasets/modality/actions"}],"tasks":[{"name":"Pose Estimation","url":"/task/pose-estimation","datasets_with_task":"/datasets/task/pose-estimation"}],"languages":[],"variants":["OmniLab"],"data_loaders":[],"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."}