Omkar2118/datasets huggingface dataset:
BlendMimic3D
Full name: A Synthetic Dataset for Human Pose Estimation

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.

Introducing paper: 3D Human Pose Estimation with Occlusions: Introducing BlendMimic3D Dataset and GCN Refinement