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We introduce PLIKS (Pseudo-Linear Inverse Kinematic Solver) forreconstruction of a 3D mesh of the human body from a single 2D image. Currenttechniques directly regress the shape, pose, and translation of a parametricmodel from an input image through a non-linear mapping with minimal flexibilityto any external influences. We approach the task as a model-in-the-loopoptimization problem. PLIKS is built on a linearized formulation of theparametric SMPL model. Using PLIKS, we can analytically reconstruct the humanmodel via 2D pixel-aligned vertices. This enables us with the flexibility touse accurate camera calibration information when available. PLIKS offers aneasy way to introduce additional constraints such as shape and translation. Wepresent quantitative evaluations which confirm that PLIKS achieves moreaccurate reconstruction with greater than 10% improvement compared to otherstate-of-the-art methods with respect to the standard 3D human pose and shapebenchmarks while also obtaining a reconstruction error improvement of 12.9 mmon the newer AGORA dataset.

PLIKS: A Pseudo-Linear Inverse Kinematic Solver for 3D Human Body Estimation