In recent decades the vision community has witnessed remarkable progress in visual
recognition partially owing to advancements in dataset benchmarks. Notably the established …

In this paper, we present PRISM, a P romptable and R obust I nteractive S egmentation M
odel, aiming for precise segmentation of 3D medical images. PRISM accepts various visual …

In this paper, we explore a principal method to enhance image segmentation quality through
limited user interaction. We propose a model solution called the multiscale feature …

Interactive segmentation methods rely on user inputs to iteratively update the selection
mask. A click specifying the object of interest is arguably the most simple and intuitive …

Integration of diverse visual prompts like clicks, scribbles, and boxes in interactive image
segmentation significantly facilitates users' interaction as well as improves interaction …

Abstract Click-based Interactive Medical Segmentation (IMS) aims to segment target objects
under limited user interactions. Although existing deep learning-based methods achieve …

Semantic segmentation of drone images is critical to many aerial vision tasks as it provides
essential semantic details that can compensate for the lack of depth information from …

In recent years, deep learning has emerged as a powerful approach in remote sensing
applications, particularly in segmentation and classification techniques that play a crucial …

The main treatment modality for oropharyngeal cancer (OPC) is radiotherapy, where
accurate segmentation of the primary gross tumor volume (GTVp) is essential. However …

The primary objective of interactive medical image segmentation systems is to achieve more
precise segmentation outcomes with reduced human intervention. This endeavor holds …