High Fidelity 3D Reconstructions with Limited Physical Views
In collaboration with Carnegie Mellon University
AuthorsMosam Dabhi, Chaoyang Wang, Kunal Saluja, Laszlo A. Jeni, Ian Fasel, Simon Lucey
Multi-view triangulation is the gold standard for 3D reconstruction from 2D correspondences, given known calibration and sufficient views. However in practice expensive multi-view setups — involving tens sometimes hundreds of cameras — are required to obtain the high fidelity 3D reconstructions necessary for modern applications. In this work we present a novel approach that leverages recent advances in 2D-3D lifting using neural shape priors while also enforcing multi-view equivariance. We show that our method can achieve comparable fidelity to expensive calibrated multi-view rigs using a limited (2-3) number of uncalibrated camera views.