Search Results for author:
Found 2 papers, 0 papers with code
IDEAL: Independent Domain Embedding Augmentation Learning
Our IDEAL with MS loss also achieves the new state-of-the-art performance on three image retrieval benchmarks, \ie, \emph{Cars-196}, \emph{CUB-200}, and \emph{SOP}.
Deep Variational Luenberger-type Observer for Stochastic Video Prediction
Our model builds upon an variational encoder which transforms the input video into a latent feature space and a Luenberger-type observer which captures the dynamic evolution of the latent features.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
