As basic research, it has also received increasing attention from people that the “curse of
dimensionality” will lead to increase the cost of data storage and computing; it also …

Feature selection, as a data preprocessing strategy, has been proven to be effective and
efficient in preparing data (especially high-dimensional data) for various data-mining and …

Single image haze removal is a challenging ill-posed problem. Existing methods use
various constraints/priors to get plausible dehazing solutions. The key to achieve haze …

A family of loss functions built on pair-based computation have been proposed in the
literature which provide a myriad of solutions for deep metric learning. In this pa-per, we …

Person re-identification (re-ID) has become increasingly popular in the community due to its
application and research significance. It aims at spotting a person of interest in other …

Graph embedding algorithms embed a graph into a vector space where the structure and
the inherent properties of the graph are preserved. The existing graph embedding methods …

Sentence embeddings are an important component of many natural language processing
(NLP) systems. Like word embeddings, sentence embeddings are typically learned on large …

Abstract Domain generalization aims to learn a classification model from multiple source
domains and generalize it to unseen target domains. A critical problem in domain …

Recently, GAN has successfully contributed to making single-image super-resolution (SISR)
methods produce more realistic images. However, natural images have complex distribution …

As one of the most successful applications of image analysis and understanding, face
recognition has recently received significant attention, especially during the past several …