Search Results for author: Nikita Durasov

Found 7 papers, 2 papers with code

ZigZag: Universal Sampling-free Uncertainty Estimation Through Two-Step Inference

no code implementations21 Nov 2022 Nikita Durasov, Nik Dorndorf, Pascal Fua

Sampling-free approaches can be faster but suffer from other drawbacks, such as lower reliability of uncertainty estimates, difficulty of use, and limited applicability to different types of tasks and data.

How to Boost Face Recognition with StyleGAN?

1 code implementation18 Oct 2022 Artem Sevastopolsky, Yury Malkov, Nikita Durasov, Luisa Verdoliva, Matthias Nießner

Our self-supervised strategy is the most useful with limited amounts of labeled training data, which can be beneficial for more tailored face recognition tasks and when facing privacy concerns.

Face Recognition

DEBOSH: Deep Bayesian Shape Optimization

no code implementations28 Sep 2021 Nikita Durasov, Artem Lukoyanov, Jonathan Donier, Pascal Fua

Shape optimization is at the heart of many industrial applications, such as aerodynamics, heat transfer, and structural analysis.

Leveraging Self-Supervision for Cross-Domain Crowd Counting

no code implementations CVPR 2022 Weizhe Liu, Nikita Durasov, Pascal Fua

State-of-the-art methods for counting people in crowded scenes rely on deep networks to estimate crowd density.

Crowd Counting

Masksembles for Uncertainty Estimation

1 code implementation CVPR 2021 Nikita Durasov, Timur Bagautdinov, Pierre Baque, Pascal Fua

Our central intuition is that there is a continuous spectrum of ensemble-like models of which MC-Dropout and Deep Ensembles are extreme examples.

Ensemble Learning Out-of-Distribution Detection +1

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