Semi-Supervised Exploration in Image Retrieval
Cheng Chang, Himanshu Rai, Satya Krishna Gorti, Junwei Ma, Chundi Liu, Guang Wei Yu, Maksims Volkovs · arXiv (Cornell University) · 2019
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.