Content-Based Video Retrieval (CBVR) is a method for searching and retrieving videos based on their intrinsic content features, bypassing the need for metadata or user- generated tags. This involves extracting spatial, temporal, and audio features, creating efficient indexes, and employing similarity metrics for retrieval. Challenges include computational complexity and addressing the semantic gap. Advancements in deep learning, particularly convolutional and recurrent neural networks, contribute to overcoming these challenges. CBVR stands as a pivotal area in research, offering a solution for efficient video retrieval in large databases with diverse content. Content- Based Video Retrieval (CBVR) using semantic segmentation involves leveraging advanced computer vision techniques to understand and retrieve videos based on their semantic content. Semantic segmentation aims to identify and classify objects or regions within an image or video frame, providing a more detailed understanding | A shadcn/ui and v0 generation - v0
