6 citations · 10 across the 12 of their papers we have counts for
15 papers
CycleCap: Improving VLMs Captioning Performance via Self-Supervised Cycle Consistency Fine-Tuning
Marios Krestenitis, Christos Tzelepis, Konstantinos Ioannidis +5
Visual-Language Models (VLMs) have achieved remarkable progress in image captioning, visual question answering, and visual reasoning. Yet they remain prone to vision-language misal…
Multi-scale Image Super Resolution with a Single Auto-Regressive Model
Enrique Sanchez, Isma Hadji, Adrian Bulat +3
In this paper we tackle Image Super Resolution (ISR), using recent advances in Visual Auto-Regressive (VAR) modeling. VAR iteratively estimates the residual in latent space between…
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…
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…
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…