A professor from Nanyang Technological University (NTU), Singapore gave a talk at MBZUAI about "Just-Noticeable Difference (JND)" models in visual intelligence. The talk covered visual JND models, research and applications, and future opportunities for JND modeling. JND can help tackle big data challenges with limited resources by focusing on user-centric and green systems. Why it matters: Exploring JND could lead to advancements in AI applications related to visual signal processing, image synthesis, and generative AI in the region.
Based solely on its title, the research paper "Exploring Visual Context for Weakly Supervised Person Search" investigates methods for leveraging visual cues to improve person search capabilities. This work explores advancements in weakly supervised learning techniques for identifying individuals across different image or video frames. The publication is associated with The Association for the Advancement of Artificial Intelligence (AAAI), indicating a contribution to the broader AI research community. Why it matters: Improvements in person search technology are vital for applications in security, surveillance, and intelligent systems, which have significant implications for smart city initiatives and public safety in the region.