In this paper, we introduce an anchor-box free and single shot instance segmentation
method, which is conceptually simple, fully convolutional and can be used by easily …

Reducing the complexity of the pipeline of instance segmentation is crucial for real-world
applications. This work addresses this issue by introducing an anchor-box free and single …

Instance segmentation is a fundamental vision task that aims to recognize and segment
each object in an image. However, it requires costly annotations such as bounding boxes …

To date, instance segmentation is dominated by two-stage methods, as pioneered by Mask
R-CNN. In contrast, one-stage alternatives cannot compete with Mask R-CNN in mask AP …

Instance segmentation aims to detect and segment individual objects in a scene. Most
existing methods rely on precise mask annotations of every category. However, it is difficult …

Effectively keeping boundary of the mask complete is important in instance segmentation. In
this task, many works segment instance based on a bounding box from the box head, which …

We present a high-performance method that can achieve mask-level instance segmentation
with only bounding-box annotations for training. While this setting has been studied in the …

End-to-end paradigms significantly improve the accuracy of various deep-learning-based
computer vision models. To this end, tasks like object detection have been upgraded by …

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 …

Given the wide diffusion of deep neural network architectures for computer vision tasks,
several new applications are nowadays more and more feasible. Among them, a particular …