Expediting Building Footprint Extraction from High-resolution Remote Sensing Images via progressive lenient supervision

arXiv:2307.12220v2 Announce Type: replace
Abstract: The efficacy of building footprint segmentation from remotely sensed images has been hindered by model transfer effectiveness. Many existing building segmentation methods were developed upon the encoder-decoder architecture of U-Net, in which the encoder is finetuned from the newly developed backbone networks that are pre-trained on ImageNet. However, the heavy computational burden of the existing decoder designs hampers the successful transfer of these modern encoder networks to remote sensing tasks. Even the widely-adopted deep supervision …

abstract architecture arxiv building cs.ai cs.cv decoder encoder encoder-decoder extraction images networks resolution segmentation sensing supervision transfer type via