755 citations · 1.4k across the 26 of their papers we have counts for
17 papers · 1 filter
Environment-Aware Satellite Image Generation with Diffusion Models
Nikos Kostagiolas, Pantelis Georgiades, Yannis Panagakis +1
Diffusion-based foundation models have recently garnered much attention in the field of generative modeling due to their ability to generate images of high quality and fidelity. Al…
Enabling Local Editing in Diffusion Models by Joint and Individual Component Analysis
Theodoros Kouzelis, Manos Plitsis, Mihalis A. Nicolaou +1
Recent advances in Diffusion Models (DMs) have led to significant progress in visual synthesis and editing tasks, establishing them as a strong competitor to Generative Adversarial…
Multilinear Mixture of Experts: Scalable Expert Specialization through Factorization
James Oldfield, Markos Georgopoulos, Grigorios G. Chrysos +5
The Mixture of Experts (MoE) paradigm provides a powerful way to decompose dense layers into smaller, modular computations often more amenable to human interpretation, debugging, a…
Locality-preserving Directions for Interpreting the Latent Space of Satellite Image GANs
Georgia Kourmouli, Nikos Kostagiolas, Yannis Panagakis +1
We present a locality-aware method for interpreting the latent space of wavelet-based Generative Adversarial Networks (GANs), that can well capture the large spatial and spectral v…
Parts of Speech-Grounded Subspaces in Vision-Language Models
James Oldfield, Christos Tzelepis, Yannis Panagakis +2
Latent image representations arising from vision-language models have proved immensely useful for a variety of downstream tasks. However, their utility is limited by their entangle…
Unsupervised Discovery of Semantic Concepts in Satellite Imagery with Style-based Wavelet-driven Generative Models
Nikos Kostagiolas, Mihalis A. Nicolaou, Yannis Panagakis
In recent years, considerable advancements have been made in the area of Generative Adversarial Networks (GANs), particularly with the advent of style-based architectures that addr…
PandA: Unsupervised Learning of Parts and Appearances in the Feature Maps of GANs
James Oldfield, Christos Tzelepis, Yannis Panagakis +2
Recent advances in the understanding of Generative Adversarial Networks (GANs) have led to remarkable progress in visual editing and synthesis tasks, capitalizing on the rich seman…
Tensor Component Analysis for Interpreting the Latent Space of GANs
James Oldfield, Markos Georgopoulos, Yannis Panagakis +2
This paper addresses the problem of finding interpretable directions in the latent space of pre-trained Generative Adversarial Networks (GANs) to facilitate controllable image synt…
Tensor Methods in Computer Vision and Deep Learning
Yannis Panagakis, Jean Kossaifi, Grigorios G. Chrysos +4
Tensors, or multidimensional arrays, are data structures that can naturally represent visual data of multiple dimensions. Inherently able to efficiently capture structured, latent…
Enhancing Facial Data Diversity with Style-based Face Aging
Markos Georgopoulos, James Oldfield, Mihalis A. Nicolaou +2
A significant limiting factor in training fair classifiers relates to the presence of dataset bias. In particular, face datasets are typically biased in terms of attributes such as…
Multimodal Joint Emotion and Game Context Recognition in League of Legends Livestreams
Charles Ringer, James Alfred Walker, Mihalis A. Nicolaou
Video game streaming provides the viewer with a rich set of audio-visual data, conveying information both with regards to the game itself, through game footage and audio, as well a…
3DFaceGAN: Adversarial Nets for 3D Face Representation, Generation, and Translation
Stylianos Moschoglou, Stylianos Ploumpis, Mihalis Nicolaou +2
Over the past few years, Generative Adversarial Networks (GANs) have garnered increased interest among researchers in Computer Vision, with applications including, but not limited…
Adversarial Learning of Disentangled and Generalizable Representations for Visual Attributes
James Oldfield, Yannis Panagakis, Mihalis A. Nicolaou
Recently, a multitude of methods for image-to-image translation have demonstrated impressive results on problems such as multi-domain or multi-attribute transfer. The vast majority…
Deep Unsupervised Multi-View Detection of Video Game Stream Highlights
Charles Ringer, Mihalis A. Nicolaou
We consider the problem of automatic highlight-detection in video game streams. Currently, the vast majority of highlight-detection systems for games are triggered by the occurrenc…
Deep Affect Prediction in-the-wild: Aff-Wild Database and Challenge, Deep Architectures, and Beyond
Dimitrios Kollias, Panagiotis Tzirakis, Mihalis A. Nicolaou +5
Automatic understanding of human affect using visual signals is of great importance in everyday human-machine interactions. Appraising human emotional states, behaviors and reactio…
Multi-Attribute Robust Component Analysis for Facial UV Maps
Stylianos Moschoglou, Evangelos Ververas, Yannis Panagakis +2
Recently, due to the collection of large scale 3D face models, as well as the advent of deep learning, a significant progress has been made in the field of 3D face alignment "in-th…
End-to-End Multimodal Emotion Recognition using Deep Neural Networks
Panagiotis Tzirakis, George Trigeorgis, Mihalis A. Nicolaou +2
Automatic affect recognition is a challenging task due to the various modalities emotions can be expressed with. Applications can be found in many domains including multimedia retr…