All instance perception tasks aim at finding certain objects specified by some queries such
as category names, language expressions, and target annotations, but this complete field …

Visual segmentation seeks to partition images, video frames, or point clouds into multiple
segments or groups. This technique has numerous real-world applications, such as …

The heavy reliance on data is one of the major reasons that currently limit the development
of deep learning. Data quality directly dominates the effect of deep learning models, and the …

Building footprint is a primary dataset of an urban geographic information system (GIS)
database. Therefore, it is essential to establish a robust and automated framework for large …

Two-stage and query-based instance segmentation methods have achieved remarkable
results. However, their segmented masks are still very coarse. In this paper, we present …

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 …

Open-vocabulary instance segmentation aims at segmenting novel classes without mask
annotations. It is an important step toward reducing laborious human supervision. Most …

The goal of interactive image segmentation is to delineate specific regions within an image
via visual or language prompts. Low-latency and high-quality interactive segmentation with …

The representative instance segmentation methods mostly segment different object
instances with a mask of the fixed resolution, eg, 28x 28 grid. However, a low-resolution …

Weakly supervised instance segmentation using only bounding box annotations has
recently attracted much research attention. Most of the current efforts leverage low-level …