5 papers
Optimizing the Consumption of Spiking Neural Networks with Activity Regularization
Simon Narduzzi, Siavash A. Bigdeli, Shih-Chii Liu +1
Reducing energy consumption is a critical point for neural network models running on edge devices. In this regard, reducing the number of multiply-accumulate (MAC) operations of De…
Privacy-Preserving Image Acquisition Using Trainable Optical Kernel
Yamin Sepehri, Pedram Pad, Pascal Frossard +1
Preserving privacy is a growing concern in our society where sensors and cameras are ubiquitous. In this work, for the first time, we propose a trainable image acquisition method t…
Leveraging Spatial and Photometric Context for Calibrated Non-Lambertian Photometric Stereo
David Honzátko, Engin Türetken, Pascal Fua +1
The problem of estimating a surface shape from its observed reflectance properties still remains a challenging task in computer vision. The presence of global illumination effects…
Learning Generative Models using Denoising Density Estimators
Siavash A. Bigdeli, Geng Lin, Tiziano Portenier +2
Learning probabilistic models that can estimate the density of a given set of samples, and generate samples from that density, is one of the fundamental challenges in unsupervised…
Image Restoration using Plug-and-Play CNN MAP Denoisers
Siavash Bigdeli, David Honzátko, Sabine Süsstrunk +1
Plug-and-play denoisers can be used to perform generic image restoration tasks independent of the degradation type. These methods build on the fact that the Maximum a Posteriori (M…