New Medium article; Query-Based Pairwise Human-Object Interaction Detection with Transformers (QPIC)(Explained)
Imagine a bustling city street captured by a surveillance camera: pedestrians crossing paths, vehicles maneuvering through traffic, cyclists weaving between lanes, and street vendors interacting with customers. For a computer vision system to make sense of this scene, it needs to not only detect the humans and objects present but also understand their interactions. This complex task is known as Human-Object Interaction (HOI) detection, a critical component for applications like autonomous driving, robotic assistance, and advanced surveillance systems.
Traditional HOI detection methods have made significant strides but still grapple with challenges such as capturing contextual nuances and accurately distinguishing overlapping interactions. Enter QPIC (Query-Based Pairwise Human-Object Interaction Detection with Image-Wide Contextual Information), introduced by researchers at Hitachi in 2021. Leveraging the power of transformers — a game-changing architecture in deep learning — QPIC sets a new standard in HOI detection by addressing the limitations of conventional approaches.