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---
license: cc-by-nc-4.0
language:
- en
---
# Model Card for Sapiens
<!-- Provide a quick summary of what the model is/does. -->
Sapiens is a family of vision transformers pretrained on 300 million human images at 1024 x 1024 image resolution.\
The pretrained models when finetuned for human-centric vision tasks generalize to in-the-wild conditions.
## Model Details
### Model Description
Sapiens, a family of models for four fundamental human-centric vision tasks - 2D pose estimation, body-part segmentation, depth estimation, and surface normal prediction.
Our models natively support 1K high-resolution inference and are extremely easy to adapt for individual tasks by simply fine-tuning models pretrained on over 300 million in-the-wild human images.
The resulting models exhibit remarkable generalization to in-the-wild data, even when labeled data is scarce or entirely synthetic.
Our simple model design also brings scalability - model performance across tasks improves as we scale the parameters from 0.3 to 2 billion.
Sapiens consistently surpasses existing baselines across various human-centric benchmarks.
- **Developed by:** Meta
- **Model type:** Vision Transformers
- **License:** Creative Commons Attribution-NonCommercial 4.0
### Model Sources
<!-- Provide the basic links for the model. -->
- **Repository:** https://github.com/facebookresearch/sapiens
- **Paper:** https://arxiv.org/abs/2408.12569
<!-- - **Demo [optional]:** [More Information Needed] -->
## Uses
- pose estimation (keypoints 17, keypoints 133, keypoints 308)
- body-part segmentation (28 classes)
- depth estimation
- surface normal estimation |