Learnable Triangulation of Human Pose

Understand

We present two novel solutions for multi-view 3D human pose estimation based on new learnable triangulation methods that combine 3D information from multiple 2D views.

• The first (baseline) solution is a basic differentiable algebraic triangulation with an addition of confidence weights estimated from the input images.
• The second solution is based on a novel method of volumetric aggregation from intermediate 2D backbone feature maps.
• The aggregated volume is then refined via 3D convolutions that produce final 3D joint heatmaps and allow modelling a human pose prior.