6 papers
Mixture of Dynamical Variational Autoencoders for Multi-Source Trajectory Modeling and Separation
Xiaoyu Lin, Laurent Girin, Xavier Alameda-Pineda
In this paper, we propose a latent-variable generative model called mixture of dynamical variational autoencoders (MixDVAE) to model the dynamics of a system composed of multiple m…
Unsupervised speech enhancement with deep dynamical generative speech and noise models
Xiaoyu Lin, Simon Leglaive, Laurent Girin +1
This work builds on a previous work on unsupervised speech enhancement using a dynamical variational autoencoder (DVAE) as the clean speech model and non-negative matrix factorizat…
Speech Modeling with a Hierarchical Transformer Dynamical VAE
Xiaoyu Lin, Xiaoyu Bie, Simon Leglaive +2
The dynamical variational autoencoders (DVAEs) are a family of latent-variable deep generative models that extends the VAE to model a sequence of observed data and a corresponding…
DSR: Towards Drone Image Super-Resolution
Xiaoyu Lin, Baran Ozaydin, Vidit Vidit +2
Despite achieving remarkable progress in recent years, single-image super-resolution methods are developed with several limitations. Specifically, they are trained on fixed content…
Towards Robust Drone Vision in the Wild
Xiaoyu Lin
The past few years have witnessed the burst of drone-based applications where computer vision plays an essential role. However, most public drone-based vision datasets focus on det…
Unsupervised Multiple-Object Tracking with a Dynamical Variational Autoencoder
Xiaoyu Lin, Laurent Girin, Xavier Alameda-Pineda
In this paper, we present an unsupervised probabilistic model and associated estimation algorithm for multi-object tracking (MOT) based on a dynamical variational autoencoder (DVAE…