UniCD unifies supervised, weakly-supervised, and unsupervised change detection via a shared encoder and collaborative branches, claiming large accuracy gains in low-supervision settings on datasets like LEVIR-CD.
Exploring effective priors and efficient models for weakly-supervised change detection.arXiv preprint arXiv:2307.10853
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Bridging Supervision Gaps: A Unified Framework for Remote Sensing Change Detection
UniCD unifies supervised, weakly-supervised, and unsupervised change detection via a shared encoder and collaborative branches, claiming large accuracy gains in low-supervision settings on datasets like LEVIR-CD.