Výsledky vyhledávání - "Dexheimer, Eric"

Report

Autor: Dexheimer, Eric, Davison, Andrew J.

We present COMO, a real-time monocular mapping and odometry system that encodes dense geometry via a compact set of 3D anchor points. Decoding anchor point projections into dense geometry via per-keyframe depth covariance functions guarantees that de

Externí odkaz: http://arxiv.org/abs/2404.03531

Zobrazit plný text záznamu

Report

Learning a Depth Covariance Function

Autor: Dexheimer, Eric, Davison, Andrew J.

We propose learning a depth covariance function with applications to geometric vision tasks. Given RGB images as input, the covariance function can be flexibly used to define priors over depth functions, predictive distributions given observations, a

Externí odkaz: http://arxiv.org/abs/2303.12157

Zobrazit plný text záznamu

Report

LEO: Learning Energy-based Models in Factor Graph Optimization

Autor: Sodhi, Paloma, Dexheimer, Eric, Mukadam, Mustafa, Anderson, Stuart, Kaess, Michael

We address the problem of learning observation models end-to-end for estimation. Robots operating in partially observable environments must infer latent states from multiple sensory inputs using observation models that capture the joint distribution

Externí odkaz: http://arxiv.org/abs/2108.02274

Zobrazit plný text záznamu