Scene graph is a structured representation of a scene that can clearly express the objects,
attributes, and relationships between objects in the scene. As computer vision technology …

Deep learning techniques have led to remarkable breakthroughs in the field of generic
object detection and have spawned a lot of scene-understanding tasks in recent years …

Existing research addresses scene graph generation (SGG)—a critical technology for scene
understanding in images—from a detection perspective, ie., objects are detected using …

Scene graph generation is an important visual understanding task with a broad range of
vision applications. Despite recent tremendous progress, it remains challenging due to the …

Traditional scene graph generation methods are trained using cross-entropy losses that
treat objects and relationships as independent entities. Such a formulation, however …

Abstract Scene Graph Generation (SGG) remains a challenging visual understanding task
due to its compositional property. Most previous works adopt a bottom-up two-stage or a …

This paper presents a fully convolutional scene graph generation (FCSGG) model that
detects objects and relations simultaneously. Most of the scene graph generation …

Knowledge Graphs (KGs) play a pivotal role in advancing various AI applications, with the
semantic web community's exploration into multi-modal dimensions unlocking new avenues …

Prior knowledge integration helps identify semantic entities and their relationships in a
graphical representation, however, its meaningful abstraction and intervention remain …

Scene Graph Generation (SGG) aims to detect the objects and their pairwise predicates in
an image. Existing SGG methods mainly fulfil the challenging predicate prediction task that …