103 citations · 209 across the 16 of their papers we have counts for
31 papers
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…
Semi-supervised learning made simple with self-supervised clustering
Enrico Fini, Pietro Astolfi, Karteek Alahari +4
Self-supervised learning models have been shown to learn rich visual representations without requiring human annotations. However, in many real-world scenarios, labels are partiall…
Robust Audio-Visual Instance Discrimination via Active Contrastive Set Mining
Hanyu Xuan, Yihong Xu, Shuo Chen +4
The recent success of audio-visual representation learning can be largely attributed to their pervasive property of audio-visual synchronization, which can be used as self-annotate…
HiT-DVAE: Human Motion Generation via Hierarchical Transformer Dynamical VAE
Xiaoyu Bie, Wen Guo, Simon Leglaive +3
Studies on the automatic processing of 3D human pose data have flourished in the recent past. In this paper, we are interested in the generation of plausible and diverse future hum…
Uncertainty-aware Contrastive Distillation for Incremental Semantic Segmentation
Guanglei Yang, Enrico Fini, Dan Xu +5
A fundamental and challenging problem in deep learning is catastrophic forgetting, i.e. the tendency of neural networks to fail to preserve the knowledge acquired from old tasks wh…
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…