Human Object Interaction
Human-object interaction (HOI) research focuses on understanding and modeling how humans interact with objects in images and videos, aiming to accurately detect, classify, and even generate these interactions. Current research emphasizes developing robust models, often leveraging transformer architectures and diffusion models, to handle challenges like occlusion, diverse object categories, and limited training data, particularly in zero-shot and few-shot learning scenarios. This field is crucial for advancing computer vision, robotics, and human-computer interaction, with applications ranging from improved activity recognition and virtual/augmented reality to more intuitive human-robot collaboration and assistive technologies. The development of large-scale, high-quality datasets with detailed annotations is also a significant area of focus.
Papers
Articulated 3D Human-Object Interactions from RGB Videos: An Empirical Analysis of Approaches and Challenges
Sanjay Haresh, Xiaohao Sun, Hanxiao Jiang, Angel X. Chang, Manolis Savva
Graphing the Future: Activity and Next Active Object Prediction using Graph-based Activity Representations
Victoria Manousaki, Konstantinos Papoutsakis, Antonis Argyros