Large-Scale Image Retrieval with Attentive Deep Local Features

ICCV 2017 Hyeonwoo NohAndre AraujoJack SimTobias WeyandBohyung Han

We propose an attentive local feature descriptor suitable for large-scale image retrieval, referred to as DELF (DEep Local Feature). The new feature is based on convolutional neural networks, which are trained only with image-level annotations on a landmark image dataset... (read more)

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Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT LEADERBOARD
Image Retrieval Oxf105k DELF+FT+ATT+DIR+QE MAP 88.5% # 2
Image Retrieval Oxf105k DELF+FT+ATT MAP 82.6% # 4
Image Retrieval Oxf5k DELF+FT+ATT+DIR+QE MAP 90.0% # 2
Image Retrieval Oxf5k DELF+FT+ATT MAP 83.8% # 4
Image Retrieval Par106k DELF+FT+ATT+DIR+QE mAP 92.8% # 2
Image Retrieval Par106k DELF+FT+ATT mAP 81.7% # 4
Image Retrieval Par6k DELF+FT+ATT+DIR+QE mAP 95.7% # 2
Image Retrieval Par6k DELF+FT+ATT mAP 85.0% # 6

Methods used in the Paper


METHOD TYPE
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