With the exponential surge in diverse multi-modal data, traditional uni-...
Massive key performance indicators (KPIs) are monitored as multivariate ...
Zero-Shot Learning (ZSL) aims to recognize unseen classes by generalizin...
Previous question-answer pair generation methods aimed to produce fluent...
The recommendation algorithm based on knowledge graphs is at a relativel...
Recently, Meta AI Research approaches a general, promptable Segment Anyt...
Multimedia applications are often associated with cross-domain knowledge...
Over the past decade, domain adaptation has become a widely studied bran...
Zero-Shot Learning has been a highlighted research topic in both vision ...
In this work, we study the black-box targeted attack problem from the mo...
Brands are facing heightened consumer pressure to address social issues ...
We aim for source-free domain adaptation, where the task is to deploy a ...
Zero-shot learning is a learning regime that recognizes unseen classes b...
Generalized Zero-Shot Learning (GZSL) aims to recognize images from both...
Growing interests in RGB-D salient object detection (RGB-D SOD) have bee...
Text revision refers to a family of natural language generation tasks, w...
Synthetic data construction of Grammatical Error Correction (GEC) for
no...
Zero-shot learning (ZSL) aims to recognize unseen classes based on the
k...
Domain adaptive semantic segmentation is recognized as a promising techn...
Deep neural networks have a clear degradation when applying to the unsee...
This paper focuses on a new problem of estimating human pose and shape f...
Hashing learns compact binary codes to store and retrieve massive data
e...
Energy disaggregation, also known as non-intrusive load monitoring (NILM...
Spectral approximation and variational inducing learning for the Gaussia...
Generalized Zero-Shot Learning (GZSL) is the task of leveraging semantic...
Fractures are widely developed in hydrocarbon reservoirs and constitute ...
Different from the traditional recommender system, the session-based
rec...
Unsupervised Domain Adaptation (UDA) aims to generalize the knowledge le...
Recently, some researches are devoted to the topic of end-to-end learnin...
In conversational machine reading, systems need to interpret natural lan...
Generalized Zero-Shot Learning (GZSL) aims to recognize images from both...
Compared to conventional zero-shot learning (ZSL) where recognising unse...
Recommendation efficiency and data sparsity problems have been regarded ...
Domain adaptation (DA) becomes an up-and-coming technique to address the...
Document interpretation and dialog understanding are the two major chall...
Zero-shot learning (ZSL) is commonly used to address the very pervasive
...
Benefiting from the spatial cues embedded in depth images, recent progre...
In this work, we present TGLS, a novel framework to unsupervised Text
Ge...
Social network stores and disseminates a tremendous amount of user share...
Rapid development of big data and high-performance computing have encour...
Supervised cross-modal hashing aims to embed the semantic correlations o...
Hashing is an effective technique to address the large-scale recommendat...
Tens of millions of women suffer from infertility worldwide each year. I...
Question generation (QG) is the task of generating a question from a
ref...
Existing methods using generative adversarial approaches for Zero-Shot
L...
Domain adaptation investigates the problem of cross-domain knowledge tra...
Lately, generative adversarial networks (GANs) have been successfully ap...
A natural language interface (NLI) to databases is an interface that
tra...
Visual paragraph generation aims to automatically describe a given image...
Domain adaptation investigates the problem of leveraging knowledge from ...