6 papers
SPARK: Input-Conditioned Sparse Activation Modulation for Frozen DiT-based Super-Resolution
Federico Putamorsi, Leonardo Zini, Marcella Cornia +1
Real-world image super-resolution (SR) increasingly relies on Diffusion Transformer (DiT) backbones, whose internal activations can be dominated by a small number of massive channe…
SVG-Score: Human-Aligned Evaluation of Text-to-SVG Generation
Marco Cipriano, Leonardo Zini, Alexandra Schild +5
Scalable Vector Graphics (SVG) generation is attracting increasing attention as generative models improve in expressiveness and controllability. Progress, however, is held back by…
A Scalable Vector Graphics Latent Space
Leonardo Zini, Elia Frigieri, Lorenzo Baraldi
Scalable Vector Graphics are a fundamental medium for resolution-independent visual content, yet the deep learning community lacks a continuous, dense, and invertible latent space…
Diffusion Language Models: An Experimental Analysis
Thomas Bertolani, Davide Bucciarelli, Leonardo Zini +2
Large Language Models (LLMs) have revolutionized language modeling through autoregressive generation, enabling strong performance across a wide range of tasks. Recently, Diffusion…
GramSR: Visual Feature Conditioning for Diffusion-Based Super-Resolution
Fabio D'Oronzio, Federico Putamorsi, Leonardo Zini +2
Despite recent advances, single-image super-resolution (SR) remains challenging, especially in real-world scenarios with complex degradations. Diffusion-based SR methods, particula…
SVGauge: Towards Human-Aligned Evaluation for SVG Generation
Leonardo Zini, Elia Frigieri, Sebastiano Aloscari +4
Generated Scalable Vector Graphics (SVG) images demand evaluation criteria tuned to their symbolic and vectorial nature: criteria that existing metrics such as FID, LPIPS, or CLIPS…