Neural Codes for Image Retrieval
Abstract
It has been shown that the activations invoked by an image within the top layers of a large convolutional neural network provide a high-level descriptor of the visual content of the image. In this paper, we investigate the use of such descriptors (neural codes) within the image retrieval application. In the experiments with several standard retrieval benchmarks, we establish that neural codes perform competitively even when the convolutional neural network has been trained for an unrelated classification task (e.g. Image-Net). We also evaluate the improvement in the retrieval performance of neural codes, when the network is retrained on a dataset of images that are similar to images encountered at test time.
Cite
Text
Babenko et al. "Neural Codes for Image Retrieval." European Conference on Computer Vision, 2014. doi:10.1007/978-3-319-10590-1_38Markdown
[Babenko et al. "Neural Codes for Image Retrieval." European Conference on Computer Vision, 2014.](https://mlanthology.org/eccv/2014/babenko2014eccv-neural/) doi:10.1007/978-3-319-10590-1_38BibTeX
@inproceedings{babenko2014eccv-neural,
title = {{Neural Codes for Image Retrieval}},
author = {Babenko, Artem and Slesarev, Anton and Chigorin, Alexander and Lempitsky, Victor S.},
booktitle = {European Conference on Computer Vision},
year = {2014},
pages = {584-599},
doi = {10.1007/978-3-319-10590-1_38},
url = {https://mlanthology.org/eccv/2014/babenko2014eccv-neural/}
}