  We present a retrieval based system for landmark retrieval and recognition
challenge.There are five parts in retrieval competition system, including
feature extraction and matching to get candidates queue; database augmentation
and query extension searching; reranking from recognition results and local
feature matching. In recognition challenge including: landmark and non-landmark
recognition, multiple recognition results voting and reranking using
combination of recognition and retrieval results. All of models trained and
predicted by PaddlePaddle framework. Using our method, we achieved 2nd place in
the Google Landmark Recognition 2019 and 2nd place in the Google Landmark
Retrieval 2019 on kaggle. The source code is available at here.
