Image segmentation, which has become a research hotspot in the field of image processing
and computer vision, refers to the process of dividing an image into meaningful and non …

Image segmentation refers to the process to divide an image into meaningful non-
overlapping regions according to human perception, which has become a classic topic since …

In this article, we model a set of pixelwise object segmentation tasks—automatic video
segmentation (AVS), image co-segmentation (ICS) and few-shot semantic segmentation …

This work proposes a novel attentive graph neural network (AGNN) for zero-shot video
object segmentation (ZVOS). The suggested AGNN recasts this task as a process of iterative …

Low-shot learning methods for image classification support learning from sparse data. We
extend these techniques to support dense semantic image segmentation. Specifically, we …

Humans tend to mine objects by learning from a group of images or several frames of video
since we live in a dynamic world. In the computer vision area, many researchers focus on co …

Grasping objects by a specific subpart is often crucial for safety and for executing
downstream tasks. We propose LERF-TOGO, Language Embedded Radiance Fields for …

Co-saliency is used to discover the common saliency on the multiple images, which is a
relatively underexplored area. In this paper, we introduce a new cluster-based algorithm for …

This paper addresses unsupervised discovery and localization of dominant objects from a
noisy image collection with multiple object classes. The setting of this problem is fully …

Image segmentation is a fundamental problem in computer vision. Despite many years of
research, general purpose image segmentation is still a very challenging task because …