244 citations · 252 across the 5 of their papers we have counts for
6 papers
Universal Marginaliser for Deep Amortised Inference for Probabilistic Programs
Robert Walecki, Kostis Gourgoulias, Adam Baker +7
Probabilistic programming languages (PPLs) are powerful modelling tools which allow to formalise our knowledge about the world and reason about its inherent uncertainty. Inference…
SEWA DB: A Rich Database for Audio-Visual Emotion and Sentiment Research in the Wild
Jean Kossaifi, Robert Walecki, Yannis Panagakis +10
Natural human-computer interaction and audio-visual human behaviour sensing systems, which would achieve robust performance in-the-wild are more needed than ever as digital devices…
Universal Marginalizer for Amortised Inference and Embedding of Generative Models
Robert Walecki, Albert Buchard, Kostis Gourgoulias +6
Probabilistic graphical models are powerful tools which allow us to formalise our knowledge about the world and reason about its inherent uncertainty. There exist a considerable nu…
Deep Structured Learning for Facial Action Unit Intensity Estimation
Robert Walecki, Ognjen, Rudovic +3
We consider the task of automated estimation of facial expression intensity. This involves estimation of multiple output variables (facial action units --- AUs) that are structural…
DeepCoder: Semi-parametric Variational Autoencoders for Automatic Facial Action Coding
Dieu Linh Tran, Robert Walecki, Ognjen Rudovic +3
Human face exhibits an inherent hierarchy in its representations (i.e., holistic facial expressions can be encoded via a set of facial action units (AUs) and their intensity). Vari…
Variable-state Latent Conditional Random Fields for Facial Expression Recognition and Action Unit Detection
Robert Walecki, Ognjen Rudovic, Vladimir Pavlovic +1
Automated recognition of facial expressions of emotions, and detection of facial action units (AUs), from videos depends critically on modeling of their dynamics. These dynamics ar…