Image instance segmentation involves labeling pixels of images with classes and instances,
which is one of the pivotal technologies in many domains, such as natural scenes …

As a challenging task in computer vision, instance segmentation has attracted extensive
attention in recent years. Able to obtain very rich and refined object information, this …

Instance segmentation in 3D scenes is fundamental in many applications of scene
understanding. It is yet challenging due to the compound factors of data irregularity and …

In recent years, instance segmentation has become a key research area in computer vision.
This technology has been applied in varied applications such as robotics, healthcare and …

Current state-of-the-art instance segmentation methods are not suited for real-time
applications like autonomous driving, which require fast execution times at high accuracy …

In this paper, we propose a single-shot instance segmentation method, which is simple, fast
and accurate. There are two main challenges for one-stage instance segmentation: object …

Abstract Existing Earth Vision datasets are either suitable for semantic segmentation or
object detection. In this work, we introduce the first benchmark dataset for instance …

Recently, proposal-free instance segmentation has received increasing attention due to its
concise and efficient pipeline. Generally, proposal-free methods generate instance-agnostic …

A major obstacle in instance segmentation is that existing methods often need many per-
pixel labels in order to be effective. These labels require large human effort and for certain …

We propose a simple yet effective instance segmentation framework, termed CondInst
(conditional convolutions for instance segmentation). Top-performing instance segmentation …