SynBody: Synthetic Dataset with Layered Human Models for 3D Perception

SynBody is a synthetic dataset for 3D human perception and modeling research. It was created by caizhongang and was last updated on the Hugging Face platform in November 2024. The dataset is designed to provide low-cost, large-scale data with features like a clothed parametric human model and layered human representations.

Use Cases

• Training 3D human pose estimation models based on synthetic data with layered human models.
• Developing clothed human generation algorithms based on the parametric human model feature.
• Advancing research in human body reconstruction based on the dataset's focus on 3D human modeling.
• Benchmarking perception models on diverse synthetic subjects as described in the abstract.

Strengths

• Designed to advance diversity and annotation quality for human models.
• Includes a clothed parametric human model for generating a diverse range of subjects.
• Features layered human representations, as mentioned in the description.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count, file formats, and dataset size are unknown, which may limit suitability assessment.
• License information is unknown, which could restrict usage.

Provenance

Source

huggingface

Collection Method

Synthetically generated, as described in the abstract.

Time Range

null

Freshness

Last updated 2024-11-04 09:30:08; freshness should be verified.

Geography

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