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Daniele Faccio

4 accepted papers

2024

Is One GPU Enough? Pushing Image Generation at Higher-Resolutions with Foundation Models.

NeurIPS 2024poster

In this work, we introduce Pixelsmith, a zero-shot text-to-image generative framework to sample images at higher resolutions with a single GPU. We are the first to show that it is possible to scale the output of a pre-trained diffusion model by a factor of 1000, opening the road to gigapixel image g…

2023

mmSense: Detecting Concealed Weapons with a Miniature Radar Sensor

ICASSP 2023accepted

For widespread adoption, public security and surveillance systems must be accurate, portable, compact, and real-time, without impeding the privacy of the individuals being observed. Current systems broadly fall into two categories – image-based which are accurate, but lack privacy, and RF signal-bas…

Cited by 0SourceScholar
2022

Bessel Equivariant Networks for Inversion of Transmission Effects in Multi-Mode Optical Fibres

NeurIPS 2022accept

We develop a new type of model for solving the task of inverting the transmission effects of multi-mode optical fibres through the construction of an $\mathrm{SO}^{+}(2,1)$-equivariant neural network. This model takes advantage of the of the azimuthal correlations known to exist in fibre speckle pat…

Cited by 3SourcePDFScholar
2018

Deep, complex, invertible networks for inversion of transmission effects in multimode optical fibres

NeurIPS 2018poster

We use complex-weighted, deep networks to invert the effects of multimode optical fibre distortion of a coherent input image. We generated experimental data based on collections of optical fibre responses to greyscale input images generated with coherent light, by measuring only image amplitude (no…