Image Retrieval On Roxford Hard

mAP

평가 결과

이 벤치마크에서 각 모델의 성능 결과

비교 표

모델 이름	mAP
large-scale-image-retrieval-with-attentive	43.1
particular-object-retrieval-with-integral-max	18.0
instance-level-image-retrieval-using	64
hypergraph-propagation-and-community	73
learning-token-based-representation-for-image	66.57
revisiting-oxford-and-paris-large-scale-image	13.2
revisiting-oxford-and-paris-large-scale-image	35.8
large-scale-image-retrieval-with-attentive	50.3
fine-tuning-cnn-image-retrieval-with-no-human	38.5
revisiting-oxford-and-paris-large-scale-image	36.4
emerging-properties-in-self-supervised-vision	24.3
learning-super-features-for-image-retrieval-1	61.2
revisiting-oxford-and-paris-large-scale-image	49.7
revisiting-oxford-and-paris-large-scale-image	36.7
google-landmarks-dataset-v2-a-large-scale	51.6
particular-object-retrieval-with-integral-max	32.4
revisiting-oxford-and-paris-large-scale-image	35.4
learning-and-aggregating-deep-local	56.9
cross-dimensional-weighting-for-aggregated	13.3
revisiting-oxford-and-paris-large-scale-image	41.3
global-features-are-all-you-need-for-image	80.2
2408-03282	80
aggregating-deep-convolutional-features-for	12.4