Search Results for author: Miguel Jaques

Found 4 papers, 2 papers with code

Vision-based system identification and 3D keypoint discovery using dynamics constraints

no code implementations13 Sep 2021 Miguel Jaques, Martin Asenov, Michael Burke, Timothy Hospedales

This paper introduces V-SysId, a novel method that enables simultaneous keypoint discovery, 3D system identification, and extrinsic camera calibration from an unlabeled video taken from a static camera, using only the family of equations of motion of the object of interest as weak supervision.

Camera Calibration

NewtonianVAE: Proportional Control and Goal Identification from Pixels via Physical Latent Spaces

no code implementations CVPR 2021 Miguel Jaques, Michael Burke, Timothy Hospedales

Learning low-dimensional latent state space dynamics models has been a powerful paradigm for enabling vision-based planning and learning for control.

Behavioural cloning

Physics-as-Inverse-Graphics: Unsupervised Physical Parameter Estimation from Video

1 code implementation ICLR 2020 Miguel Jaques, Michael Burke, Timothy Hospedales

Our approach significantly outperforms related unsupervised methods in long-term future frame prediction of systems with interacting objects (such as ball-spring or 3-body gravitational systems), due to its ability to build dynamics into the model as an inductive bias.

Inductive Bias Model Predictive Control +2

Efficient variational Bayesian neural network ensembles for outlier detection

1 code implementation20 Mar 2017 Nick Pawlowski, Miguel Jaques, Ben Glocker

In this work we perform outlier detection using ensembles of neural networks obtained by variational approximation of the posterior in a Bayesian neural network setting.

Outlier Detection

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