DC-TTA improves interactive segmentation accuracy by partitioning user clicks into subsets for independent test-time adaptation of SAM models and merging the specialized predictors.
Real-time, accurate, and consistent video semantic segmentation via unsupervised adaptation and cross-unit de- ployment on mobile device
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2025 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
DC-TTA: Divide-and-Conquer Framework for Test-Time Adaptation of Interactive Segmentation
DC-TTA improves interactive segmentation accuracy by partitioning user clicks into subsets for independent test-time adaptation of SAM models and merging the specialized predictors.