Babenko et al. demonstrate the usage of deep convolutional neural networks, based on the architecture by Krizhevsky et al. , for image retrieval. They report promising results, especially when re-training networks on appropriate datasets and using different compression techniques. Unfortunately, the implementation as well as the dataset for re-training are not publicly available - merely a list (in Russian) corresponding to the keywords used for the Yandex search engine is provided (see here). However, Babenko et al. claim that a custom version of the original implementation (available here) by Krizhevsky et al. is used. The effectiveness of different layers for image retrieval is compared to several state-of-the-art approaches [2,3,4,5].
What is your opinion on the summarized work? Or do you know related work that is of interest? Let me know your thoughts in the comments below or using the following platforms: