Object detection or localization is an incremental step in progression from coarse to fine
digital image inference. It not only provides the classes of the image objects, but also …

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 …

Prevalent state-of-the-art instance segmentation methods fall into a query-based scheme, in
which instance masks are derived by querying the image feature using a set of instance …

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

Instance segmentation is one of the fundamental vision tasks. Recently, fully convolutional
instance segmentation methods have drawn much attention as they are often simpler and …

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 …

We present a simple, fully-convolutional model for real-time instance segmentation that
achieves 29.8 mAP on MS COCO at 33.5 fps evaluated on a single Titan Xp, which is …

Cascade is a classic yet powerful architecture that has boosted performance on various
tasks. However, how to introduce cascade to instance segmentation remains an open …

Resembling the rapid learning capability of human, low-shot learning empowers vision
systems to understand new concepts by training with few samples. Leading approaches …

Letting a deep network be aware of the quality of its own predictions is an interesting yet
important problem. In the task of instance segmentation, the confidence of instance …