Given an untrimmed video, temporal sentence grounding (TSG) aims to locate a target
moment semantically according to a sentence query. Although previous respectable works …

View missing and label missing are two challenging problems in the applications of multi-
view multi-label classification scenery. In the past years, many efforts have been made to …

Due to the rapid development of multimedia technology and sensor technology, multi-view
clustering (MVC) has become a research hotspot in machine learning, data mining, and …

In recent years, multi-view multi-label learning has aroused extensive research enthusiasm.
However, multi-view multi-label data in the real world is commonly incomplete due to the …

Incomplete multi-view clustering (IMVC) aims to partition samples into different groups for
datasets with missing samples. The primary goal of IMVC is to effectively address the …

Graph-based multi-view clustering has attracted extensive attention because of the powerful
clustering-structure representation ability and noise robustness. Considering the reality of a …

As we all know, multi-view data is more expressive than single-view data and multi-label
annotation enjoys richer supervision information than single-label, which makes multi-view …

Unsupervised domain adaptive object detection (UDA-OD) aims to learn a detector by
generalizing knowledge from a labeled source domain to an unlabeled target domain …

In the area of clustering, multi-view clustering has drawn a lot of research attention by
making full use of information from different views. In many practical applications, collecting …

Multimodal fusion focuses on integrating information from multiple modalities with the goal of
more accurate prediction, which has achieved remarkable progress in a wide range of …