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 …

Object detection as a subfield within computer vision has achieved remarkable progress,
which aims to accurately identify and locate a specific object from images or videos. Such …

We propose an agglomerative Transformer (AGER) that enables Transformer-based human-
object interaction (HOI) detectors to flexibly exploit extra instance-level cues in a single …

Recently, the DETR framework has emerged as the dominant approach for human--object
interaction (HOI) research. In particular, two-stage transformer-based HOI detectors are …

Abstract Human Object Interaction (HOI) detection aims to localize and infer the
relationships between a human and an object. Arguably, training supervised models for this …

Detecting human-object interaction (HOI) has long been limited by the amount of supervised
data available. Recent approaches address this issue by pre-training according to pseudo …

Few-shot object detection (FSOD) identifies objects from extremely few annotated samples.
Most existing FSOD methods, recently, apply the two-stage learning paradigm, which …

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 …

Single-stage Human-Object Interaction (HOI) detection methods have attracted considerable
attention due to their high efficiency. Existing methods tend to concentrate the detection of …

Power line inspection based on UAVs can effectively improve the inspection efficiency. With
the development of object detection algorithms, automatic detection and recognition for …