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This article discusses the use of deep learning methods, such as CNNs and transformers, in solving the image-retrieval problem in visual place recognition (VPR). These methods are more robust to changes in lighting, weather, and viewpoint and have shown promising results in location recognition research. The article also mentions specific techniques, such as NetVLAD and GeM pooling, that have been successful in VPR.
