Semantic Completion

Semantic completion focuses on reconstructing missing or incomplete information within a data modality, often by leveraging information from other modalities or general semantic knowledge. Current research emphasizes cross-modal alignment, particularly in vision-language tasks, using techniques like masked modeling and attention mechanisms to fill in gaps in images, videos, or text. These advancements improve performance in applications such as image and video retrieval, visual question answering, and 3D scene reconstruction, demonstrating the practical value of robust semantic completion methods. Furthermore, research explores the role of semantic completion in cognitive processes like episodic memory, suggesting broader implications for understanding human memory and information processing.