5 papers
Training-Free Generation of Diverse and High-Fidelity Images via Prompt Semantic Space Optimization
Debin Meng, Chen Jin, Zheng Gao +3
Image diversity remains a fundamental challenge for text-to-image diffusion models. Low-diversity models tend to generate repetitive outputs, increasing sampling redundancy and hin…
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…
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…
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…
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…