DataCube: A Video Retrieval Platform via Natural Language Semantic Profiling

2026-02-18

AI Summary

This work addresses the high cost and low efficiency associated with constructing high-quality, task-specific video datasets from large-scale video collections. To overcome these challenges, the authors propose an intelligent video retrieval platform that leverages multidimensional semantic modeling to generate deep semantic representations of video clips. The system integrates hybrid retrieval based on natural language queries with a neural re-ranking mechanism to enable precise and efficient construction of customized video subsets. Users can interactively build private retrieval systems through natural language interfaces, and the platform is publicly accessible via a web interface. This approach significantly enhances the efficiency and flexibility of video dataset curation for training, analysis, and evaluation purposes.

Technology Category

• Computer Vision: Image and Video Retrieval
• Data Mining & Knowledge Management: Conversational Systems for Recommendation & Retrieval
• Intelligent Robots: Multimodal Perception & Sensor Fusion

Application Category

• Search and Retrieval-Augmented AI: Vertical and domain-specific search
• User Modeling, Personalization and Recommendation: Fairness-aware retrieval and ranking
• Graph Algorithms and Modeling for the Web: Querying, indexing, and retrieval in Web-related graphs

Abstract

Large-scale video repositories are increasingly available for modern video understanding and generation tasks. However, transforming raw videos into high-quality, task-specific datasets remains costly and inefficient. We present DataCube, an intelligent platform for automatic video processing, multi-dimensional profiling, and query-driven retrieval. DataCube constructs structured semantic representations of video clips and supports hybrid retrieval with neural re-ranking and deep semantic matching. Through an interactive web interface, users can efficiently construct customized video subsets from massive repositories for training, analysis, and evaluation, and build searchable systems over their own private video collections. The system is publicly accessible at https://datacube.baai.ac.cn/. Demo Video: https://baai-data-cube.ks3-cn-beijing.ksyuncs.com/custom/Adobe%20Express%20-%202%E6%9C%8818%E6%97%A5%20%281%29%281%29%20%281%29.mp4

Problem

• video retrieval
• semantic profiling
• dataset construction
• large-scale video repositories
• task-specific datasets

Innovation

• video retrieval
• semantic profiling
• neural re-ranking
• structured representation
• interactive platform