facebookresearch/sapiens

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5418 stars · 321 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Sapiens is a family of foundation models from Meta Reality Labs for human-centric vision tasks including 2D pose estimation, body-part segmentation, depth estimation, and surface normal prediction. The models are pretrained on 300 million in-the-wild human images, natively support 1K high-resolution inference, and scale from 0.3 to 2 billion parameters.

Use cases

• estimate 2D human pose from images
• segment human body parts in photos
• predict monocular depth for people in images
• predict surface normals of human bodies
• fine-tune human vision models on custom datasets
• extract high-resolution human features for avatar creation

When to choose

• you need state-of-the-art human-centric vision models with strong generalization
• you work with high-resolution (1K) human imagery
• you have limited labeled data and want strong pretrained backbones
• you need multiple human vision tasks from one model family

When to avoid

• you need general object detection or non-human vision tasks
• you lack GPU resources for billion-parameter models
• you need a lightweight model for edge or mobile deployment
• you require a permissive license without restrictions

Facets

library · maturity active

computer-vision image-processing machine-learning deep-learning computer-vision deep-learning artificial-intelligence python pose-estimation depth-estimation surface-normals segmentation human-vision eccv-2024 pretrained-models gpu linux

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