Scene graphs are powerful abstractions that capture relationships between objects in
images by modeling objects as nodes and relationships as edges. Generation of realistic …

Graph embedding is an important technique used for representing graph structure data that
preserves intrinsic features in a low-dimensional space suitable for graph-based …

Negative sampling plays a crucial role in training successful sequential recommendation
models. Instead of merely employing random negative sample selection, numerous …

Image search engines enable the retrieval of images relevant to a query image. In this work,
we consider the setting where a query for similar images is derived from a collection of …

Scene classification and recognition have always been one of the most challenging tasks of
scene understanding due to the inherent ambiguity in visual scenes. The core of scene …

Scene graph generation (SGG) has been developed to detect objects and their relationships
from the visual data and has attracted increasing attention in recent years. Existing works …

Summarization tasks aim to summarize multiple pieces of information into a short description
or representative information. A text summarization task summarizes textual information into …

With the rapid development of web services, various kinds of context data become available
in recommender systems to handler the data sparsity problem, called context-aware …

We consider the cross-modal task of producing color representations for text phrases.
Motivated by the fact that a significant fraction of user queries on an image search engine …

Abstract Information-rich BIM models are rarely usable off-the-shelf for operations tasks.
Change decisions made on the construction site can lead to significant differences between …