Invisible Human

"Invisible human" research encompasses efforts to address scenarios where humans are undetected or their presence is incompletely perceived by systems, whether due to physical occlusion, limitations in sensing technology, or adversarial manipulation. Current research focuses on developing algorithms and models, such as reinforcement learning frameworks for contract design, physics-guided restoration networks for terahertz imaging, and generative adversarial networks for creating adversarial patches, to improve detection and prediction of unseen humans or mitigate their invisibility. These advancements have significant implications for robotics, security, and medical imaging, enabling safer and more robust systems that account for the presence of potentially unseen individuals in various contexts.