THREE-DIMENSIONAL OBJECT SHAPE AND MOTION ESTIMATION FROM SPATIOTEMPORAL DATA WITH DIFFUSION GUIDED MODELS

Abstract

Systems, methods, and apparatuses for estimating a three-dimensional (3D) object. One apparatus includes at least one electronic processor and at least one memory storing a machine learning model and instructions executable by the at least one electronic processor. The machine learning model trained to receive an initial estimate of a set of model parameters corresponding to the 3D object and generated using a regression model, based on an input image, perform denoising diffusion implicit model (DDIM) inversion on the initial estimate to obtain a latent representation, generate, using a diffusion model and a score guidance term, a refined latent representation by iteratively applying a guided sampling process, and generate a refined estimate of the set of model parameters based on the refined latent representation.

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