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Found 3 papers, 3 papers with code
FOUND: Foot Optimization with Uncertain Normals for Surface Deformation Using Synthetic Data
Our FOUND approach tackles this, with 4 main contributions: (i) SynFoot, a synthetic dataset of 50, 000 photorealistic foot images, paired with ground truth surface normals and keypoints; (ii) an uncertainty-aware surface normal predictor trained on our synthetic dataset; (iii) an optimization scheme for fitting a generative foot model to a series of images; and (iv) a benchmark dataset of calibrated images and high resolution ground truth geometry.
FIND: An Unsupervised Implicit 3D Model of Articulated Human Feet
In this paper we present a high fidelity and articulated 3D human foot model.
Who Left the Dogs Out? 3D Animal Reconstruction with Expectation Maximization in the Loop
We introduce an automatic, end-to-end method for recovering the 3D pose and shape of dogs from monocular internet images.
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