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arXiv · 1906.04944

Semi-Supervised Exploration in Image Retrieval

Cheng Chang·Himanshu Rai·Satya Krishna Gorti·Junwei Ma·Chundi Liu·Guangwei Yu·Maksims Volkovs
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Abstract

We present our solution to Landmark Image Retrieval Challenge 2019. This challenge was based on the large Google Landmarks Dataset V2[9]. The goal was to retrieve all database images containing the same landmark for every provided query image. Our solution is a combination of global and local models to form an initial KNN graph. We then use a novel extension of the recently proposed graph traversal method EGT [1] referred to as semi-supervised EGT to refine the graph and retrieve better candidates.

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Cheng Chang, Himanshu Rai, Satya Krishna Gorti, Junwei Ma, Chundi Liu, Guangwei Yu, Maksims Volkovs. 2019-06-12. Semi-Supervised Exploration in Image Retrieval. https://arxiv.org/abs/1906.04944

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