SegPAR, a class-centric decision-based sparse attack with a discrepancy reward, outperforms black-box sparse baselines in semantic segmentation MIoU reduction and sparsity efficiency.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
baseline 1
citation-polarity summary
fields
cs.CV 1years
2026 1verdicts
CONDITIONAL 1roles
baseline 1polarities
baseline 1representative citing papers
citing papers explorer
-
SegPAR: Class-Centric Decision-Based Sparse Attack for Semantic Segmentation
SegPAR, a class-centric decision-based sparse attack with a discrepancy reward, outperforms black-box sparse baselines in semantic segmentation MIoU reduction and sparsity efficiency.