most citedInverting Gradients -- How easy is it to break privacy in federated learning?

207 citations · 208 across the 3 of their papers we have counts for

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cs.CV2024

VHS: High-Resolution Iterative Stereo Matching with Visual Hull Priors

Markus Plack, Hannah Dröge, Leif Van Holland +1

We present a stereo-matching method for depth estimation from high-resolution images using visual hulls as priors, and a memory-efficient technique for the correlation computation.…

cs.CV2020★ 207 cited

Inverting Gradients -- How easy is it to break privacy in federated learning?

Jonas Geiping, Hartmut Bauermeister, Hannah Dröge +1

The idea of federated learning is to collaboratively train a neural network on a server. Each user receives the current weights of the network and in turns sends parameter updates…