This research introduces a novel approach to Reasoning Segmentation (RS) that enables AI systems to identify and segment objects based on complex text queries without step-by-step instructions.

• Implements just-in-time digital twins to enhance reasoning capabilities
• Overcomes limitations of current multimodal LLMs in visual perception
• Enables multi-step reasoning for complex object identification in videos
• Improves temporal consistency and spatial accuracy in video analysis

Security Applications: This technology significantly enhances surveillance and monitoring systems by allowing security personnel to use natural language queries to identify suspicious objects or activities across video feeds, improving threat detection without requiring explicit programming for each scenario.

Original Paper: Online Reasoning Video Segmentation with Just-in-Time Digital Twins