Black-Box Face Recovery from Identity Features

In this work, we present a novel algorithm based on an it-erative sampling of random Gaussian blobs for black-box face recovery,given only an output feature vector of deep face recognition systems. Weattack the state-of-the-art face recognition system (ArcFace) to test ouralgorithm. Another network with different architecture (FaceNet) is usedas an independent critic showing that the target person can be identi-fied with the reconstructed image even with no access to the attackedmodel. Furthermore, our algorithm requires a significantly less numberof queries compared to the state-of-the-art solution.