# CNN-VWII: An Efficient Approach for Large-Scale Video Retrieval by Image Queries

arXiv: https://arxiv.org/abs/1810.06030 · HTML: https://mlsanity.com/paper/1810.06030/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Oct 2018.

## Built on by (most cited first, 1 of 1)

- [A multimodal deep learning framework for scalable content based visual media retrieval](https://mlsanity.com/paper/2105.08665/) (2021)

## Abstract (arXiv)

This paper aims to solve the problem of large-scale video retrieval by a query image. Firstly, we define the problem of top-k image to video query. Then, we combine the merits of convolutional neural networks(CNN for short) and Bag of Visual Word(BoVW for short) module to design a model for video frames information extraction and representation. In order to meet the requirements of large-scale video retrieval, we proposed a visual weighted inverted index(VWII for short) and related algorithm to improve the efficiency and accuracy of retrieval process. Comprehensive experiments show that our proposed technique achieves substantial improvements (up to an order of magnitude speed up) over the state-of-the-art techniques with similar accuracy.