Image segmentation is a key task in computer vision and image processing with important
applications such as scene understanding, medical image analysis, robotic perception …

The synergistic combination of deep learning (DL) models and Earth observation (EO)
promises significant advances to support the Sustainable Development Goals (SDGs). New …

Diffusion Probabilistic Methods are employed for state-of-the-art image generation. In this
work, we present a method for extending such models for performing image segmentation …

This paper introduces a novel contour-based approach named deep snake for real-time
instance segmentation. Unlike some recent methods that directly regress the coordinates of …

Manually labeling objects by tracing their boundaries is a laborious process. In Polygon-
RNN++, the authors proposed Polygon-RNN that produces polygonal annotations in a …

This paper addresses the problem of semi-supervised transfer learning with limited cross-
modality data in remote sensing. A large amount of multi-modal earth observation images …

While most state-of-the-art instance segmentation methods produce binary segmentation
masks, geographic and cartographic applications typically require precise vector polygons …

In this paper, we propose PolyTransform, a novel instance segmentation algorithm that
produces precise, geometry-preserving masks by combining the strengths of prevailing …

Deep learning based methods have significantly boosted the study of automatic building
extraction from remote sensing images. However, delineating vectorized and regular …

Deep learning methods based upon convolutional neural networks (CNNs) have
demonstrated impressive performance in the task of building outline delineation from very …