As an interesting and emerging topic, co-saliency detection aims at simultaneously
extracting common salient objects from a group of images. On one hand, traditional co …

A weakly supervised semantic segmentation (WSSS) method aims to learn a segmentation
model from weak (image-level) as opposed to strong (pixel-level) labels. By avoiding the …

Image semantic segmentation is the task of partitioning image into several regions based on
semantic concepts. In this paper, we learn a weakly supervised semantic segmentation …

Hierarchical image segmentation is a prevalent technique in the literature for improving
segmentation quality, where the segmentation result needs to be searched at different …

The task of semantic segmentation is to obtain strong pixel‐level annotations for each pixel
in the image. For fully supervised semantic segmentation, the task is achieved by a …

Rich high-quality annotated data is critical for semantic segmentation learning, yet acquiring
dense and pixel-wise ground-truth is both labor-and time-consuming. Coarse annotations …

Semantic segmentation can provide basic semantic information for scene understanding,
which has important theoretical research value and broad application prospects. Limited by …

The task of semantic segmentation is to infer a predefined category label for each pixel in
the image. For most cases, image segmentation is established as a fully supervised task …

Marine organism datasets often present sparse annotated labels and with many objects in
cluttered background. Therefore, there are two challenges to do image segmentation on …

弱监督语义分割任务常利用训练集中全体图像的超像素及其相似度建立图模型,
使用图像级别标记的监督关系进行约束求解. 全局建模缺少单幅图像结构信息 …