SUR-LID selects replay samples that approximate each task's global feature distribution and trains per-task classifiers aligned by angularity, improving incremental face forgery detection.
Memory aware synapses: Learning what (not) to forget
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2024 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Stacking Brick by Brick: Aligned Feature Isolation for Incremental Face Forgery Detection
SUR-LID selects replay samples that approximate each task's global feature distribution and trains per-task classifiers aligned by angularity, improving incremental face forgery detection.