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SURREAL Dataset

Synthetic hUmans foR REAL tasks

SURREAL Dataset

First large-scale person dataset to generate depth, body parts, optical flow, 2D/3D pose, surface normals ground truth for RGB video input. The dataset contains 6M frames of synthetic humans. The images are photo-realistic renderings of people under large variations in shape, texture, view-point and pose. To ensure realism, the synthetic bodies are created using the SMPL body model, whose parameters are fit by the MoSh method given raw 3D MoCap marker data.

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Task
Human Pose Estimation
Annotation Types
Keypoint Skeleton
6000000
Items
6
Classes
6000000
Labels
Models using this dataset
Last updated on 
January 20, 2022
Licensed under 
Research Only