activity
20212024
most citedVisual Speech-Aware Perceptual 3D Facial Expression Reconstruction from Videos

7 citations · 13 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2024

Mushroom Segmentation and 3D Pose Estimation from Point Clouds using Fully Convolutional Geometric Features and Implicit Pose Encoding

George Retsinas, Niki Efthymiou, Petros Maragos

Modern agricultural applications rely more and more on deep learning solutions. However, training well-performing deep networks requires a large amount of annotated data that may n…

cs.LG2023

Matrix Factorization in Tropical and Mixed Tropical-Linear Algebras

Ioannis Kordonis, Emmanouil Theodosis, George Retsinas +1

Matrix Factorization (MF) has found numerous applications in Machine Learning and Data Mining, including collaborative filtering recommendation systems, dimensionality reduction, d…

cs.CV2023

Photorealistic and Identity-Preserving Image-Based Emotion Manipulation with Latent Diffusion Models

Ioannis Pikoulis, Panagiotis P. Filntisis, Petros Maragos

In this paper, we investigate the emotion manipulation capabilities of diffusion models with "in-the-wild" images, a rather unexplored application area relative to the vast and rap…

cs.CV2023

ViDaS Video Depth-aware Saliency Network

Ioanna Diamanti, Antigoni Tsiami, Petros Koutras +1

We introduce ViDaS, a two-stream, fully convolutional Video, Depth-Aware Saliency network to address the problem of attention modeling ``in-the-wild", via saliency prediction in vi…

cs.CV20235 cited

Medical Face Masks and Emotion Recognition from the Body: Insights from a Deep Learning Perspective

Nikolaos Kegkeroglou, Panagiotis P. Filntisis, Petros Maragos

The COVID-19 pandemic has undoubtedly changed the standards and affected all aspects of our lives, especially social communication. It has forced people to extensively wear medical…

eess.AS2023

Multi-Source Contrastive Learning from Musical Audio

Christos Garoufis, Athanasia Zlatintsi, Petros Maragos

Contrastive learning constitutes an emerging branch of self-supervised learning that leverages large amounts of unlabeled data, by learning a latent space, where pairs of different…