{"url":"/dataset/blendmimic3d-a-synthetic-dataset-for-human","name":"BlendMimic3D","full_name":"A Synthetic Dataset for Human Pose Estimation","description_markdown":"BlendMimic3D is a pioneering synthetic dataset developed using Blender, designed to enhance Human Pose Estimation (HPE) research. This dataset features diverse scenarios including self-occlusions, object-based occlusions, and out-of-frame occlusions, tailored for the development and testing of advanced HPE models.\r\n\r\nMain features:\r\n\r\n* Realistic Environments: BlendMimic3D encompasses simple environments, resembling Human3.6M dataset, shopping activities and multi-person contexts, simulating real-world environments.\r\n* Diverse Occlusion Scenarios: Specifically addresses self-occlusions, object-based occlusions, and out-of-frame occlusions.\r\n* Multi-Perspective Capture: Utilizes four cameras to capture diverse human movements and interactions from multiple angles.\r\n* Pixel-Perfect Annotations: Offers detailed annotations for 2D keypoints, 3D keypoints, and occlusion data.","description_withheld":null,"homepage":"https://github.com/FilipaLino/BlendMimic3D","introduced_date":"2024-04-24","introduced_date_note":null,"introduced_by":{"paper":"/paper/3d-human-pose-estimation-with-occlusions","title":"3D Human Pose Estimation with Occlusions: Introducing BlendMimic3D Dataset and GCN Refinement","first_author":"Filipa Lino","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"3D Human Pose Estimation","url":"/task/3d-human-pose-estimation","datasets_with_task":"/datasets/task/3d-human-pose-estimation"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["BlendMimic3D"],"data_loaders":[],"num_papers_in_archive":2,"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":"2026-09-25T09:33:49+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."}