19 citations · 28 across the 5 of their papers we have counts for
5 papers
DreamCache: Finetuning-Free Lightweight Personalized Image Generation via Feature Caching
Emanuele Aiello, Umberto Michieli, Diego Valsesia +2
Personalized image generation requires text-to-image generative models that capture the core features of a reference subject to allow for controlled generation across different con…
MotionCraft: Physics-based Zero-Shot Video Generation
Luca Savant Aira, Antonio Montanaro, Emanuele Aiello +2
Generating videos with realistic and physically plausible motion is one of the main recent challenges in computer vision. While diffusion models are achieving compelling results in…
Jointly Training Large Autoregressive Multimodal Models
Emanuele Aiello, Lili Yu, Yixin Nie +2
In recent years, advances in the large-scale pretraining of language and text-to-image models have revolutionized the field of machine learning. Yet, integrating these two modaliti…
Fast Inference in Denoising Diffusion Models via MMD Finetuning
Emanuele Aiello, Diego Valsesia, Enrico Magli
Denoising Diffusion Models (DDMs) have become a popular tool for generating high-quality samples from complex data distributions. These models are able to capture sophisticated pat…
Cross-modal Learning for Image-Guided Point Cloud Shape Completion
Emanuele Aiello, Diego Valsesia, Enrico Magli
In this paper we explore the recent topic of point cloud completion, guided by an auxiliary image. We show how it is possible to effectively combine the information from the two mo…