8 papers
VidCLearn: A Continual Learning Approach for Text-to-Video Generation
Luca Zanchetta, Lorenzo Papa, Luca Maiano +1
Text-to-video generation is an emerging field in generative AI, enabling the creation of realistic, semantically accurate videos from text prompts. While current models achieve imp…
Shedding Light on Depth: Explainability Assessment in Monocular Depth Estimation
Lorenzo Cirillo, Claudio Schiavella, Lorenzo Papa +2
Explainable artificial intelligence is increasingly employed to understand the decision-making process of deep learning models and create trustworthiness in their adoption. However…
Enhancing Abnormality Identification: Robust Out-of-Distribution Strategies for Deepfake Detection
Luca Maiano, Fabrizio Casadei, Irene Amerini
Detecting deepfakes has become a critical challenge in Computer Vision and Artificial Intelligence. Despite significant progress in detection techniques, generalizing them to open-…
Z-SASLM: Zero-Shot Style-Aligned SLI Blending Latent Manipulation
Alessio Borgi, Luca Maiano, Irene Amerini
We introduce Z-SASLM, a Zero-Shot Style-Aligned SLI (Spherical Linear Interpolation) Blending Latent Manipulation pipeline that overcomes the limitations of current multi-style ble…
Enhancing Ground-to-Aerial Image Matching for Visual Misinformation Detection Using Semantic Segmentation
Emanuele Mule, Matteo Pannacci, Ali Ghasemi Goudarzi +4
The recent advancements in generative AI techniques, which have significantly increased the online dissemination of altered images and videos, have raised serious concerns about th…
Beyond adaptive gradient: Fast-Controlled Minibatch Algorithm for large-scale optimization
Corrado Coppola, Lorenzo Papa, Irene Amerini +1
Adaptive gradient methods have been increasingly adopted by deep learning community due to their fast convergence and reduced sensitivity to hyper-parameters. However, these method…