Learnable PINs: cross-modal embeddings for person identity
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These methods commonly investigate differences in early, middle, and late fusion, and work has been done to address view-missing and view-heterogeneity problems.
“These methods also commonly investigate differences in “early”, “middle”, and “late” fusion and work has even been done to address the view-missing and view-heterogeneity problems (Nagrani et al., 2018; Wang et al., 2020).”
From Missing data in multi-omics integration: Recent advances through artificial intelligence (2023) · cites this paper as Nagrani et al., 2018
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Flagged first, then by citations
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Cited by
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Missing data in multi-omics integration: Recent advances through artificial intelligence
Flores, J. E., Claborne, D. M., Weller, Z. D., Webb-Robertson, B.-J. M., Waters, K. M., & Bramer, L. M. (2023) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2023.1098308 · Cited by 181 · see citing works
“These methods also commonly investigate differences in “early”, “middle”, and “late” fusion and work has even been done to address the view-missing and view-heterogeneity problems (Nagrani et al., 2018; Wang et al., 2020).”
Method
- Authors
- Nagrani, A., Albanie, S., & Zisserman, A.
- Affiliations
- University of Oxford (GB)
- Corresponding author
- Nagrani, Arsha
- Venue
- Lecture notes in computer science
- Publisher
- Springer International Publishing
- Published
- 2018
- Pages
- 73-89
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2798513620
- Cited by
- 151
- References
- 59
- Citations by year
- 2026: 6 · 2025: 20 · 2024: 23 · 2023: 20 · 2022: 18 · 2021: 28 · 2020: 17 · 2019: 14 · 2018: 5
- FWCI
- 4.82
- Type
- conference paper
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- Lecture notes in computer science (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- Cambridge University Engineering Department Publications Database (submittedVersion)
- arXiv (Cornell University)
- Funders
- Engineering and Physical Sciences Research Council (EP/M013774/1)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face recognition and analysis
- Physical Sciences › Computer Science › Signal Processing › Biometric Identification and Security
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face and Expression Recognition
- Keywords
- personal identity, cross-modal retrieval, curriculum learning, hard negative mining
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