Scene Knowledge

Scene knowledge, encompassing an understanding of object relationships and contextual information within a scene, is crucial for improving the performance of various AI systems. Current research focuses on integrating scene knowledge into models through techniques like prompt-based frameworks, adversarial domain adaptation, and scene-conditioned hypernetworks, often leveraging transformer architectures and self-supervised learning. This research aims to enhance the robustness and accuracy of applications such as person re-identification, temporal video grounding, and 3D object detection, particularly in challenging scenarios with partial observability or domain shifts. The resulting advancements have significant implications for autonomous systems, robotics, and other fields requiring robust scene understanding.