MOCD combines O-Mix synthetic ambiguity samples with an HSIC debiasing loss to improve open-set recognition in multi-view classification, reporting gains over seven baselines on six datasets.
Smola, and Bernhard Schölkopf
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.CV 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
unclear 1representative citing papers
citing papers explorer
-
Enhancing Multi-view Open-set Learning via Ambiguity Uncertainty Calibration and View-wise Debiasing
MOCD combines O-Mix synthetic ambiguity samples with an HSIC debiasing loss to improve open-set recognition in multi-view classification, reporting gains over seven baselines on six datasets.