activity
20182022
most citedLearning Disentangled Representations with Reference-Based Variational Autoencoders

19 citations · 25 across the 5 of their papers we have counts for

collaborators

9 papers

cs.CV2022

Permutation-Invariant Relational Network for Multi-person 3D Pose Estimation

Nicolas Ugrinovic, Adria Ruiz, Antonio Agudo +2

The recovery of multi-person 3D poses from a single RGB image is a severely ill-conditioned problem due to the inherent 2D-3D depth ambiguity, inter-person occlusions, and body tru…

cs.CV20221 cited

Efficient Remote Photoplethysmography with Temporal Derivative Modules and Time-Shift Invariant Loss

Joaquim Comas, Adria Ruiz, Federico Sukno

We present a lightweight neural model for remote heart rate estimation focused on the efficient spatio-temporal learning of facial photoplethysmography (PPG) based on i) modelling…

cs.CV20221 cited

Conditional-Flow NeRF: Accurate 3D Modelling with Reliable Uncertainty Quantification

Jianxiong Shen, Antonio Agudo, Francesc Moreno-Noguer +1

A critical limitation of current methods based on Neural Radiance Fields (NeRF) is that they are unable to quantify the uncertainty associated with the learned appearance and geome…

cs.CV20214 cited

Stochastic Neural Radiance Fields: Quantifying Uncertainty in Implicit 3D Representations

Jianxiong Shen, Adria Ruiz, Antonio Agudo +1

Neural Radiance Fields (NeRF) has become a popular framework for learning implicit 3D representations and addressing different tasks such as novel-view synthesis or depth-map estim…

cs.CV2021

Generating Attribution Maps with Disentangled Masked Backpropagation

Adria Ruiz, Antonio Agudo, Francesc Moreno

Attribution map visualization has arisen as one of the most effective techniques to understand the underlying inference process of Convolutional Neural Networks. In this task, the…

cs.CV2020

Anytime Inference with Distilled Hierarchical Neural Ensembles

Adria Ruiz, Jakob Verbeek

Inference in deep neural networks can be computationally expensive, and networks capable of anytime inference are important in mscenarios where the amount of compute or quantity of…