Mask Pooling, which pools foreground and background separately using ground-truth masks, improves object-detection robustness on domain-shift benchmarks but requires masks at inference and lacks a rigorous causal derivation.
Scale- aware domain adaptive faster r-cnn.International Journal of Computer Vision, 129(7):2223– 2243, 2021
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
-
Mitigating Context Bias in Domain Adaptation for Object Detection using Mask Pooling
Mask Pooling, which pools foreground and background separately using ground-truth masks, improves object-detection robustness on domain-shift benchmarks but requires masks at inference and lacks a rigorous causal derivation.