To handle more complex visual scenes with a larger number of objects and their relationships, VTPrompt can be extended in several ways:
Hierarchical Key Concept Extraction: Implement a hierarchical key concept extraction approach to identify primary objects and their relationships, then extract secondary objects and their connections. This hierarchical structure can help in understanding complex scenes with multiple objects.
Object Grouping: Develop algorithms to group related objects together based on their attributes or spatial relationships. This grouping can provide a more holistic view of the scene and aid in answering questions that involve interactions between multiple objects.
Spatial Reasoning: Integrate spatial reasoning capabilities into the key concept extraction process to understand the spatial relationships between objects in the scene. This can help in answering questions that require knowledge of object positions and orientations.
Dynamic Prompt Generation: Implement dynamic prompt generation techniques that adapt to the complexity of the visual scene. By adjusting the prompts based on the scene complexity, VTPrompt can effectively handle a larger number of objects and their relationships.