Extracted Features on AmsterTime Dataset
Datacite citation style:
Yildiz, Burak; Khademi, Seyran (2022): Extracted Features on AmsterTime Dataset. Version 3. 4TU.ResearchData. dataset. https://doi.org/10.4121/14572644.v3
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset
choose version:
version 4 - 2022-06-07 (latest)
version 3 - 2022-04-12
version 2 - 2021-06-08
version 1 - 2021-05-12
CC BY 4.0
This collection contains feature files where the features are extracted on AmsterTime dataset using various methods and models such as SIFT, LIFT, and pre-trained VGG-16, ResNets, NetVLAD, AP-GeM and supervisely and self-supervisely trained models. The details of feature extraction procedure and other details can be found on https://github.com/seyrankhademi/AmsterTime.
history
- 2021-05-12 first online
- 2022-04-12 published, posted
publisher
4TU.ResearchData
format
Pickle file
associated peer-reviewed publication
AmsterTime: A Visual Place Recognition Benchmark Dataset for Severe Domain Shift
references
organizations
TU Delft, Faculty of Electrical Engineering, Mathematics and Computer Science Intelligent Systems
DATA
files (14)
- 20,282,404 bytesMD5:
91099171982d0e87ce2386b8a8f403acap_gem_landmarks.p - 2,705,170 bytesMD5:
b2c3b30a622b05f8a19eab807075dcaalift_piccadilly_128.p - 322,832,359 bytesMD5:
ce32fec7843201fc40bcdbf7ba45a8d8netvlad_pittsburgh250k.p - 20,282,404 bytesMD5:
a5a399839030986b593dcd407c834abfresnet101_imagenet.p - 20,282,404 bytesMD5:
3c264112b53e464319b34cb0f642b4c0resnet50_imagenet.p - 2,705,170 bytesMD5:
89c297423fe08eaba61c81fc437c8f75sift_128.p - 20,282,404 bytesMD5:
812e4c62b7b042f2a696212e02d4e167simsiam_resnet50_scratch_amstertime_ep10000_bs128.p - 20,282,404 bytesMD5:
2335e737bea264e62ca117717458176dsimsiam_resnet50_scratch_gldv2_ep100_bs128.p - 20,282,404 bytesMD5:
91fc99d22dd6afef11fc19d1fc846d06simsiam_resnet50_scratch_imagenet_ep100_bs256.p - 247,199,719 bytesMD5:
65e5e811533dacbdb9f2d8c4c8c7c299simsiam_vgg16_scratch_amstertime_ep10000_bs128.p - 247,199,719 bytesMD5:
13e9d4efcd279b942f80348c53bc87ccsimsiam_vgg16_scratch_gldv2_ep100_bs128.p - 247,199,719 bytesMD5:
e74387a8628fa6ec3fc676016ec1ba11simsiam_vgg16_scratch_imagenet_ep100_bs128.p - 5,153,797 bytesMD5:
883aabaf2968e4b6f23730802cad0526triplet_resnet18_imagenet.p - 247,199,719 bytesMD5:
bfd13404f9168ca3f87bb80ac267b20fvgg16_imagenet.p -
download all files (zip)
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