Flow-CDNet jointly trains an optical flow branch and a change detection branch to detect both slow displacements and fast appearance/disappearance changes in bitemporal images, reporting FEPE 0.869 on a self-built synthetic dataset.
Liteflownet: A lightweight convolutional neural network for optical flow estimation
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
background 1representative citing papers
citing papers explorer
-
Flow-CDNet: A Novel Network for Detecting Both Slow and Fast Changes in Bitemporal Images
Flow-CDNet jointly trains an optical flow branch and a change detection branch to detect both slow displacements and fast appearance/disappearance changes in bitemporal images, reporting FEPE 0.869 on a self-built synthetic dataset.