TASK	DATASET	MODEL	METRIC NAME	METRIC VALUE	GLOBAL RANK
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

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Large-Scale Image Retrieval with Attentive Deep Local Features

ICCV 2017 • Hyeonwoo Noh • Andre Araujo • Jack Sim • Tobias Weyand • Bohyung 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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tensorflow/models

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nashory/DeLF-pytorch

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insikk/delf_enhanced

jandaldrop/landmark-recognition-challenge

pandigreat/DELF

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Ranked #2 on Image Retrieval on Oxf5k

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

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Large-Scale Image Retrieval with Attentive Deep Local Features

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