April 4, 2024, 4:45 a.m. | Jie Zhu, Jirong Zha, Ding Li, Leye Wang

cs.CV updates on arXiv.org arxiv.org

arXiv:2404.02462v1 Announce Type: new
Abstract: Self-supervised learning shows promise in harnessing extensive unlabeled data, but it also confronts significant privacy concerns, especially in vision. In this paper, we aim to perform membership inference on visual self-supervised models in a more realistic setting: self-supervised training method and details are unknown for an adversary when attacking as he usually faces a black-box system in practice. In this setting, considering that self-supervised model could be trained by completely different self-supervised paradigms, e.g., masked …

arxiv capability cs.cv encoder inference part type via visual

Data Scientist (m/f/x/d)

@ Symanto Research GmbH & Co. KG | Spain, Germany

Head of Data Governance - Vice President

@ iCapital | New York City, United States

Analytics Engineer / Data Analyst (Intermediate/Senior)

@ Employment Hero | Ho Chi Minh City, Ho Chi Minh City, Vietnam - Remote

Senior Customer Data Strategy Manager (Remote, San Francisco)

@ Dynatrace | San Francisco, CA, United States

Software Developer - AI/Machine Learning

@ ICF | Nationwide Remote Office (US99)

Senior Data Science Manager - Logistics, Rider (all genders)

@ Delivery Hero | Berlin, Germany