5 citations · 7 across the 3 of their papers we have counts for
3 papers
cs.CV2020★ 5 cited
WGANVO: Monocular Visual Odometry based on Generative Adversarial Networks
Javier Cremona, Lucas Uzal, Taihú Pire
In this work we present WGANVO, a Deep Learning based monocular Visual Odometry method. In particular, a neural network is trained to regress a pose estimate from an image pair. Th…
cs.CV2019★ 2 cited
Exploiting GAN Internal Capacity for High-Quality Reconstruction of Natural Images
Marcos Pividori, Guillermo L. Grinblat, Lucas C. Uzal
Generative Adversarial Networks (GAN) have demonstrated impressive results in modeling the distribution of natural images, learning latent representations that capture semantic var…
cs.CV2019
Exploiting video sequences for unsupervised disentangling in generative adversarial networks
Facundo Tuesca, Lucas C. Uzal
In this work we present an adversarial training algorithm that exploits correlations in video to learn --without supervision-- an image generator model with a disentangled latent s…