Discrete point cloud objects lack sufficient shape descriptors of 3D geometries. In this paper,
we present a novel method for aggregating hypothetical curves in point clouds. Sequences …

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 …

3D scene graph prediction is important for intelligent agents to gather information and
perceive semantics of their environments. However, constructing an effective graph is …

The task of 3D semantic scene graph (3DSSG) prediction in the point cloud is challenging
since (1) the 3D point cloud only captures geometric structures with limited semantics …

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 …

Current approaches for 3D scene graph prediction rely on labeled datasets to train models
for a fixed set of known object classes and relationship categories. We present Open3DSG …

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

Building 3D scene graphs has recently emerged as a topic in scene representation for
several embodied AI applications to represent the world in a structured and rich manner …

Graph neural networks (GNNs) have been extensively developed for graph representation
learning in various application domains. However, similar to all other neural networks …

In the field of 3D scene understanding, 3D scene graphs have emerged as a new scene
representation that combines geometric and semantic information about objects and their …