2 citations · 2 across the 2 of their papers we have counts for
3 papers
cs.CV2022★ 2 cited
PartAL: Efficient Partial Active Learning in Multi-Task Visual Settings
Nikita Durasov, Nik Dorndorf, Pascal Fua
Multi-task learning is central to many real-world applications. Unfortunately, obtaining labelled data for all tasks is time-consuming, challenging, and expensive. Active Learning…
cs.CV2021
Leveraging Self-Supervision for Cross-Domain Crowd Counting
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. While effective, these data-driven approaches rely on large amount o…
cs.LG2020
Masksembles for Uncertainty Estimation
Nikita Durasov, Timur Bagautdinov, Pierre Baque +1
Deep neural networks have amply demonstrated their prowess but estimating the reliability of their predictions remains challenging. Deep Ensembles are widely considered as being on…