SSP-3D (Sports Shape and Pose 3D)

Introduced by Sengupta et al. in Synthetic Training for Accurate 3D Human Pose and Shape Estimation in the Wild

SSP-3D is an evaluation dataset consisting of 311 images of sportspersons in tight-fitted clothes, with a variety of body shapes and poses. The images were collected from the Sports-1M dataset. SSP-3D is intended for use as a benchmark for body shape prediction methods. Pseudo-ground-truth 3D shape labels (using the SMPL body model) were obtained via multi-frame optimisation with shape consistency between frames, as described here.

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