Image co-segmentation is important for its advantage of alleviating the ill-pose nature image segmentation through exploring correlation between related images. Many automatic algorithms have been developed in last decade, which are investigated comprehensively this paper. We firstly analyze visual/semantic cues guiding co-segmentation, including object and cues. Then, we describe traditional m...

Humans tend to mine objects by learning from a group of images or several frames video since we live in dynamic world. In the computer vision area, many researchers focus on co-segmentation (CoS), co-saliency detection (CoSD) and salient object (VSOD) discover co-occurrent objects. However, previous approaches design different networks for these similar tasks separately, they are difficult appl...

3D shape co-segmentation is an important topic in computer graphics. The idea of co-analysis brings new insights into understanding a collection of shapes. Rather than analysing individual shapes, an entire set is looked at, giving much more information about the class of shape in the set. Existing co-segmentation techniques use both face and segment level descriptors in order to provide enough...