32 citations · 47 across the 9 of their papers we have counts for
10 papers
Improving face generation quality and prompt following with synthetic captions
Michail Tarasiou, Stylianos Moschoglou, Jiankang Deng +1
Recent advancements in text-to-image generation using diffusion models have significantly improved the quality of generated images and expanded the ability to depict a wide range o…
ShapeFusion: A 3D diffusion model for localized shape editing
Rolandos Alexandros Potamias, Michail Tarasiou, Stylianos Ploumpis +1
In the realm of 3D computer vision, parametric models have emerged as a ground-breaking methodology for the creation of realistic and expressive 3D avatars. Traditionally, they rel…
Locally Adaptive Neural 3D Morphable Models
Michail Tarasiou, Rolandos Alexandros Potamias, Eimear O'Sullivan +2
We present the Locally Adaptive Morphable Model (LAMM), a highly flexible Auto-Encoder (AE) framework for learning to generate and manipulate 3D meshes. We train our architecture f…
Rethinking the Domain Gap in Near-infrared Face Recognition
Michail Tarasiou, Jiankang Deng, Stefanos Zafeiriou
Heterogeneous face recognition (HFR) involves the intricate task of matching face images across the visual domains of visible (VIS) and near-infrared (NIR). While much of the exist…
ViTs for SITS: Vision Transformers for Satellite Image Time Series
Michail Tarasiou, Erik Chavez, Stefanos Zafeiriou
In this paper we introduce the Temporo-Spatial Vision Transformer (TSViT), a fully-attentional model for general Satellite Image Time Series (SITS) processing based on the Vision T…
Embedding Earth: Self-supervised contrastive pre-training for dense land cover classification
Michail Tarasiou, Stefanos Zafeiriou
In training machine learning models for land cover semantic segmentation there is a stark contrast between the availability of satellite imagery to be used as inputs and ground tru…
DeepSatData: Building large scale datasets of satellite images for training machine learning models
Michail Tarasiou, Stefanos Zafeiriou
This report presents design considerations for automatically generating satellite imagery datasets for training machine learning models with emphasis placed on dense classification…
Context-self contrastive pretraining for crop type semantic segmentation
Michail Tarasiou, Riza Alp Guler, Stefanos Zafeiriou
In this paper, we propose a fully supervised pre-training scheme based on contrastive learning particularly tailored to dense classification tasks. The proposed Context-Self Contra…
Extracting deep local features to detect manipulated images of human faces
Michail Tarasiou, Stefanos Zafeiriou
Recent developments in computer vision and machine learning have made it possible to create realistic manipulated videos of human faces, raising the issue of ensuring adequate prot…
Synthesising 3D Facial Motion from "In-the-Wild" Speech
Panagiotis Tzirakis, Athanasios Papaioannou, Alexander Lattas +3
Synthesising 3D facial motion from speech is a crucial problem manifesting in a multitude of applications such as computer games and movies. Recently proposed methods tackle this p…