Change detection based on remote sensing (RS) data is an important method of detecting
changes on the Earth's surface and has a wide range of applications in urban planning …

Object segmentation and object tracking are fundamental research areas in the computer
vision community. These two topics are difficult to handle some common challenges, such …

Abstract We present Boundary IoU (Intersection-over-Union), a new segmentation
evaluation measure focused on boundary quality. We perform an extensive analysis across …

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 …

We present a model-agnostic post-processing scheme to improve the boundary quality for
the segmentation result that is generated by any existing segmentation model. Motivated by …

We introduce VISOR, a new dataset of pixel annotations and a benchmark suite for
segmenting hands and active objects in egocentric video. VISOR annotates videos from …

Annotating images with pixel-wise labels is a time-consuming and costly process. Recently,
DatasetGAN showcased a promising alternative-to synthesize a large labeled dataset via a …

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 …

In contrast to the fully supervised methods using pixel-wise mask labels, box-supervised
instance segmentation takes advantage of the simple box annotations, which has recently …

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