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

Abstract Scene Graph Generation (SGG) aims to detect all the visual relation triplets< sub,
pred, obj> in a given image. With the emergence of various advanced techniques for better …

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 …

Scene graph generation aims to construct a semantic graph structure from an image such
that its nodes and edges respectively represent objects and their relationships. One of the …

Scene graph generation (SGG) aims to abstract an image into a graph structure, by
representing objects as graph nodes and their relations as labeled edges. However, two …

Abstract Scene Graph Generation (SGG) aims to extract< subject, predicate, object>
relationships in images for vision understanding. Although recent works have made steady …

Scene graph generation is an important task in computer vision aimed at improving the
semantic understand-ing of the visual world. In this task, the model needs to detect objects …

Scene graph generation (SGG) is a fundamental task aimed at detecting visual relations
between objects in an image. The prevailing SGG methods require all object classes to be …

As an important visual understanding task, scene graph generation has been drawing
widespread attention and could boost a broad range of downstream vision applications …

Abstract Scene Graph Generation (SGG) offers a structured representation critical in many
computer vision applications. Traditional SGG approaches, however, are limited by a closed …