Video deduplication is a crucial process for managing large-scale video inventory, where duplicates consume storage, increase processing costs, and affect data quality negatively. 

This article explores a robust architecture for deduplication using video segmentation, frame embedding extraction, and clustering techniques. It also highlights key methodologies like video hashing, CLIP embeddings, and temporal alignment for effective deduplication.