Datasets › BlendMimic3D

BlendMimic3D (A Synthetic Dataset for Human Pose Estimation)

Introduced by Filipa Lino et al. in 3D Human Pose Estimation with Occlusions: Introducing BlendMimic3D Dataset and GCN Refinement24 Apr 2024 archive 2025-07-28

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.

Main features:

  • Realistic Environments: BlendMimic3D encompasses simple environments, resembling Human3.6M dataset, shopping activities and multi-person contexts, simulating real-world environments.
  • Diverse Occlusion Scenarios: Specifically addresses self-occlusions, object-based occlusions, and out-of-frame occlusions.
  • Multi-Perspective Capture: Utilizes four cameras to capture diverse human movements and interactions from multiple angles.
  • Pixel-Perfect Annotations: Offers detailed annotations for 2D keypoints, 3D keypoints, and occlusion data.

Benchmarks archive 2025-07-28

No leaderboard in the archive resolves to this dataset.

Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 2 papers for it but never published that list.

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

No licence recorded in the archive. Absence here is not a statement about the dataset's terms.

Modalities archive 2025-07-28

Languages archive 2025-07-28

Variants archive 2025-07-28

  • BlendMimic3D

1 variant name, as the archive lists them.

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