Searching a Raw Video Database using Natural Language Queries
The number of videos being produced and consequently stored in databases for video streaming platforms has been increasing exponentially over time. This vast database should be easily index-able to find the requisite clip or video to match the given search specification, preferably in the form of a textual query. This work aims to provide an end-to-end pipeline to search a video database with a voice query from the end user. The pipeline makes use of Recurrent Neural Networks in combination with Convolutional Neural Networks to generate captions of the video clips present in the database.
Code (0)
등록된 구현이 없습니다.
Tasks
Natural Language QueriesSimilar Papers 제목 키워드 기반
Person Search with Natural Language Description
Searching persons in large-scale image databases with the query of natural language description has important applications in video surveillance. Existing methods mainly focused on searching persons with image-based or a…
AttributePerson SearchText based Person RetrievalSearching for Better Database Queries in the Outputs of Semantic Parsers
The task of generating a database query from a question in natural language suffers from ambiguity and insufficiently precise description of the goal. The problem is amplified when the system needs to generalize to datab…
Saying What You're Looking For: Linguistics Meets Video Search
We present an approach to searching large video corpora for video clips which depict a natural-language query in the form of a sentence. This approach uses compositional semantics to encode subtle meaning that is lost in…
object-detectionObject DetectionSentenceThe End-of-End-to-End: A Video Understanding Pentathlon Challenge (2020)
We present a new video understanding pentathlon challenge, an open competition held in conjunction with the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2020. The objective of the challenge was to ex…
Natural Language QueriesRetrievalText to Video RetrievalVideo Retrieval+1Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries
Multi-modal datasets, like those involving images, often miss the detailed descriptions that properly capture the rich information encoded in each item. This makes answering complex natural language queries a major chall…
Contrastive LearningImage RetrievalNatural Language QueriesRetrieval+1