Abstract Human-Object Interaction (HOI) detection, which localizes and infers relationships
between human and objects, plays an important role in scene understanding. Although two …

Abstract Relational Language-Image Pre-training (RLIP) aims to align vision representations
with relational texts, thereby advancing the capability of relational reasoning in computer …

Human-object interaction (HOI) detection aims to comprehend the intricate relationships
between humans and objects, predicting triplets, and serving as the foundation for …

The interaction decoder utilized in prevalent Transformer-based HOI detectors typically
accepts pre-composed human-object pairs as inputs. Though achieving remarkable …

Abstract Human-Object Interaction (HOI) detection is a challenging computer vision task that
requires visual models to address the complex interactive relationship between humans and …

Unlike most previous HOI methods that focus on learning better human-object features, we
propose a novel and complementary approach called category query learning. Such queries …

In this paper we develop MP-HOI a powerful Multi-modal Prompt-based HOI detector
designed to leverage both textual descriptions for open-set generalization and visual …

Abstract Human-Object Interaction (HOI) detection is a critical topic in the visual
understanding field. With the development of deep learning models, the research of HOI …

Open-vocabulary human-object interaction (HOI) detection which is concerned with the
problem of detecting novel HOIs guided by natural language is crucial for understanding …

Abstract Zero-shot Human-Object Interaction (HOI) detection aims to identify both seen and
unseen HOI categories. A strong zero-shot HOI detector is supposed to be not only capable …