Unity-Technologies/PeopleSansPeople
Unity's privacy-preserving human-centric synthetic data generator
PeopleSansPeople helps computer vision engineers develop models for human detection and pose estimation without needing extensive real-world human data. It takes descriptions of virtual scenes with human characters and outputs large, diverse synthetic datasets complete with 2D/3D bounding boxes, segmentation masks, and human keypoint labels. This is ideal for researchers and engineers building computer vision applications that interact with people.
321 stars. No commits in the last 6 months.
Use this if you need to train or pre-train computer vision models that analyze human actions or presence, but face challenges with data privacy, collection costs, or diversity in real-world datasets.
Not ideal if your computer vision task does not involve human subjects, or if you exclusively require real-world, non-synthetic data for training and validation.
Stars
321
Forks
34
Language
C#
License
Apache-2.0
Category
Last pushed
Mar 05, 2024
Commits (30d)
0
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