Visual prompt engineering is a fundamental methodology in the field of visual and image
artificial general intelligence. As the development of large vision models progresses, the …

Fully automatic deep learning has become the state-of-the-art technique for many tasks
including image acquisition, analysis and interpretation, and for the extraction of clinically …

Interactive segmentation allows users to extract target masks by making positive/negative
clicks. Although explored by many previous works, there is still a gap between academic …

Click-based interactive image segmentation aims at extracting objects with a limited user
clicking. A hierarchical backbone is the de-facto architecture for current methods. Recently …

Recent works on click-based interactive segmentation have demonstrated state-of-the-art
results by using various inference-time optimization schemes. These methods are …

Deep neural networks have become a mainstream approach to interactive segmentation. As
we show in our experiments, while for some images a trained network provides accurate …

In click-based interactive segmentation, the mask extraction process is dictated by
positive/negative user clicks; however, most existing methods do not fully exploit the user …

High-quality training data play a key role in image segmentation tasks. Usually, pixel-level
annotations are expensive, laborious and time-consuming for the large volume of training …

In the task of interactive image segmentation, users initially click one point to segment the
main body of the target object and then provide more points on mislabeled regions …

Interactive image segmentation is an essential tool in pixel-level annotation and image
editing. To obtain a high-precision binary segmentation mask, users tend to add interaction …