11 citations · 21 across the 18 of their papers we have counts for
18 papers
TPSO: Training-Free Diverse Image Generation via Semantic Prompt Embedding Optimization
Debin Meng, Chen Jin, Zheng Gao +3
Image diversity remains a fundamental challenge for text-to-image diffusion models. Low-diversity generation often leads to repetitive outputs, increasing sampling redundancy and h…
CemiFace: Center-based Semi-hard Synthetic Face Generation for Face Recognition
Zhonglin Sun, Siyang Song, Ioannis Patras +1
Privacy issue is a main concern in developing face recognition techniques. Although synthetic face images can partially mitigate potential legal risks while maintaining effective f…
MM2Latent: Text-to-facial image generation and editing in GANs with multimodal assistance
Debin Meng, Christos Tzelepis, Ioannis Patras +1
Generating human portraits is a hot topic in the image generation area, e.g. mask-to-face generation and text-to-face generation. However, these unimodal generation methods lack co…
CLIPCleaner: Cleaning Noisy Labels with CLIP
Chen Feng, Georgios Tzimiropoulos, Ioannis Patras
Learning with Noisy labels (LNL) poses a significant challenge for the Machine Learning community. Some of the most widely used approaches that select as clean samples for which th…
Are CLIP features all you need for Universal Synthetic Image Origin Attribution?
Dario Cioni, Christos Tzelepis, Lorenzo Seidenari +1
The steady improvement of Diffusion Models for visual synthesis has given rise to many new and interesting use cases of synthetic images but also has raised concerns about their po…
Efficient Unsupervised Visual Representation Learning with Explicit Cluster Balancing
Ioannis Maniadis Metaxas, Georgios Tzimiropoulos, Ioannis Patras
Self-supervised learning has recently emerged as the preeminent pretraining paradigm across and between modalities, with remarkable results. In the image domain specifically, group…
VLLMs Provide Better Context for Emotion Understanding Through Common Sense Reasoning
Alexandros Xenos, Niki Maria Foteinopoulou, Ioanna Ntinou +2
Recognising emotions in context involves identifying an individual's apparent emotions while considering contextual cues from the surrounding scene. Previous approaches to this tas…
LAFS: Landmark-based Facial Self-supervised Learning for Face Recognition
Zhonglin Sun, Chen Feng, Ioannis Patras +1
In this work we focus on learning facial representations that can be adapted to train effective face recognition models, particularly in the absence of labels. Firstly, compared wi…
FOAA: Flattened Outer Arithmetic Attention For Multimodal Tumor Classification
Omnia Alwazzan, Ioannis Patras, Gregory Slabaugh
Fusion of multimodal healthcare data holds great promise to provide a holistic view of a patient's health, taking advantage of the complementarity of different modalities while lev…
Self-Supervised Facial Representation Learning with Facial Region Awareness
Zheng Gao, Ioannis Patras
Self-supervised pre-training has been proved to be effective in learning transferable representations that benefit various visual tasks. This paper asks this question: can self-sup…
DiffusionAct: Controllable Diffusion Autoencoder for One-shot Face Reenactment
Stella Bounareli, Christos Tzelepis, Vasileios Argyriou +2
Video-driven neural face reenactment aims to synthesize realistic facial images that successfully preserve the identity and appearance of a source face, while transferring the targ…
One-shot Neural Face Reenactment via Finding Directions in GAN's Latent Space
Stella Bounareli, Christos Tzelepis, Vasileios Argyriou +2
In this paper, we present our framework for neural face/head reenactment whose goal is to transfer the 3D head orientation and expression of a target face to a source face. Previou…
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…
Improving Fairness using Vision-Language Driven Image Augmentation
Moreno D'Incà, Christos Tzelepis, Ioannis Patras +1
Fairness is crucial when training a deep-learning discriminative model, especially in the facial domain. Models tend to correlate specific characteristics (such as age and skin col…
Machine Learning Approaches for Fine-Grained Symptom Estimation in Schizophrenia: A Comprehensive Review
Niki Maria Foteinopoulou, Ioannis Patras
Schizophrenia is a severe yet treatable mental disorder, it is diagnosed using a multitude of primary and secondary symptoms. Diagnosis and treatment for each individual depends on…
A Simple Baseline for Knowledge-Based Visual Question Answering
Alexandros Xenos, Themos Stafylakis, Ioannis Patras +1
This paper is on the problem of Knowledge-Based Visual Question Answering (KB-VQA). Recent works have emphasized the significance of incorporating both explicit (through external d…
EmoCLIP: A Vision-Language Method for Zero-Shot Video Facial Expression Recognition
Niki Maria Foteinopoulou, Ioannis Patras
Facial Expression Recognition (FER) is a crucial task in affective computing, but its conventional focus on the seven basic emotions limits its applicability to the complex and exp…
Self-Supervised Representation Learning with Cross-Context Learning between Global and Hypercolumn Features
Zheng Gao, Chen Feng, Ioannis Patras
Whilst contrastive learning yields powerful representations by matching different augmented views of the same instance, it lacks the ability to capture the similarities between dif…