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Recovering Geometric Information with Learned Texture Perturbations
(ACM, 2021)
Regularization is used to avoid overfitting when training a neural network; unfortunately, this reduces the attainable level of detail hindering the ability to capture high-frequency information present in the training ...
Three Dimensional Reconstruction of Botanical Trees with Simulatable Geometry
(ACM, 2021)
We tackle the challenging problem of creating full and accurate three dimensional reconstructions of botanical trees with the topological and geometric accuracy required for subsequent physical simulation, e.g. in response ...