Transformer is a promising neural network learner, and has achieved great success in
various machine learning tasks. Thanks to the recent prevalence of multimodal applications …

Different objects in the same scene are more or less related to each other, but only a limited
number of these relationships are noteworthy. Inspired by Detection Transformer, which …

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 …

Towards building comprehensive real-world visual perception systems, we propose and
study a new problem called panoptic scene graph generation (PVSG). PVSG is related to …

Humans can not only see the collection of objects in visual scenes, but also identify the
relationship between objects. The visual relationship in the scene can be abstracted into the …

The task of dynamic scene graph generation (SGG) from videos is complicated and
challenging due to the inherent dynamics of a scene, temporal fluctuation of model …

Video scene graph generation (VidSGG) aims to parse the video content into scene graphs,
which involves modeling the spatio-temporal contextual information in the video. However …

Panoptic Scene Graph (PSG) is a challenging task in Scene Graph Generation (SGG) that
aims to create a more comprehensive scene graph representation using panoptic …

Scene graph generation (SGG) is to detect object pairs with their relations in an image.
Existing SGG approaches often use multi-stage pipelines to decompose this task into object …

Video scene graph generation (VidSGG) aims to identify objects in visual scenes and infer
their relationships for a given video. It requires not only a comprehensive understanding of …