DataCube: A Video Retrieval Platform via Natural Language Semantic Profiling

TL;DR

DataCube is a platform that enables efficient, semantic-based video retrieval and dataset construction from large video repositories using natural language queries and structured representations.

Contribution

We introduce DataCube, a novel system for automatic semantic profiling and retrieval of videos, facilitating customized dataset creation and private collection management.

Findings

Supports hybrid neural re-ranking for accurate retrieval

Enables construction of task-specific video datasets

Accessible via an interactive web interface

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