Datasets:
ArXiv:
DOI:
License:
Commit
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Parent(s):
761d93a
Upload folder using huggingface_hub
Browse files- .gitattributes +2 -0
- README.md +9 -22
- README.txt +10 -0
- data/test_list.txt +0 -0
- data/train_list.txt +3 -0
- data/vggface2_test.tar.gz +3 -0
- data/vggface2_train.tar.gz +3 -0
- meta/bb_landmark.tar.gz +3 -0
- meta/class_overlap_vgg1_2.txt +54 -0
- meta/identity_meta.csv +0 -0
- meta/test_agetemp_imglist.txt +2000 -0
- meta/test_list.txt +0 -0
- meta/test_posetemp_imglist.txt +0 -0
- meta/train_list.txt +3 -0
- samples_0.png +3 -0
.gitattributes
CHANGED
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@@ -53,3 +53,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.jpg filter=lfs diff=lfs merge=lfs -text
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*.jpeg filter=lfs diff=lfs merge=lfs -text
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*.webp filter=lfs diff=lfs merge=lfs -text
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*.jpg filter=lfs diff=lfs merge=lfs -text
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*.jpeg filter=lfs diff=lfs merge=lfs -text
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*.webp filter=lfs diff=lfs merge=lfs -text
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data/train_list.txt filter=lfs diff=lfs merge=lfs -text
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meta/train_list.txt filter=lfs diff=lfs merge=lfs -text
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README.md
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Andrew Zisserman},
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title = {VGGFace2: {A} dataset for recognising faces across pose and age},
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journal = {CoRR},
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volume = {abs/1710.08092},
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year = {2017},
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url = {http://arxiv.org/abs/1710.08092},
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eprinttype = {arXiv},
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eprint = {1710.08092},
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timestamp = {Wed, 04 Aug 2021 07:50:14 +0200},
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biburl = {https://dblp.org/rec/journals/corr/abs-1710-08092.bib},
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bibsource = {dblp computer science bibliography, https://dblp.org}
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}
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```
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# README
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## 关于超神经 Hyper.AI
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超神经 Hyper.AI（https://hyper.ai）是科技实验媒体，专注报道人工智能与其适用场景。致力于推动中文领域对机器智能的认知与普及，探讨机器智能的对社会的影响。超神经为提高科研效率，提供大陆范围内最快最全的公开数据集下载节点、人工智能百科词条等多个产品，服务产业相关从业者和科研院所的师生。
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## 关于数据集
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- 数据集名称：VGG-Face2
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- 发布机构：牛津大学工程科学系视觉几何组 Visual Geometry Group, Department of Engineering Science, University of Oxford
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- 网址：http://www.robots.ox.ac.uk/~vgg/data/vgg_face/
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- 大小：nan GB
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- 简介：VGGFace2是一个大规模的人脸识别数据集，包含9131个人的面部。 图像从Google图片搜索下载，在姿势，年龄，照明，种族和职业方面有很大差异。该数据集于2015年由牛津大学工程科学系视觉几何组发布，相关论文为Deep Face Recognition。
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README.txt
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# README
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## 关于超神经 Hyper.AI
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+
超神经 Hyper.AI（https://hyper.ai）是科技实验媒体，专注报道人工智能与其适用场景。致力于推动中文领域对机器智能的认知与普及，探讨机器智能的对社会的影响。超神经为提高科研效率，提供大陆范围内最快最全的公开数据集下载节点、人工智能百科词条等多个产品，服务产业相关从业者和科研院所的师生。
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## 关于数据集
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- 数据集名称：VGG-Face2
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- 发布机构：牛津大学工程科学系视觉几何组 Visual Geometry Group, Department of Engineering Science, University of Oxford
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- 网址：http://www.robots.ox.ac.uk/~vgg/data/vgg_face/
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- 大小：nan GB
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- 简介：VGGFace2是一个大规模的人脸识别数据集，包含9131个人的面部。 图像从Google图片搜索下载，在姿势，年龄，照明，种族和职业方面有很大差异。该数据集于2015年由牛津大学工程科学系视觉几何组发布，相关论文为Deep Face Recognition。
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data/test_list.txt
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The diff for this file is too large to render.
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data/train_list.txt
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version https://git-lfs.github.com/spec/v1
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oid sha256:f0adf062077543c894ca91a70324454ba6a151c4ac1aec8a2b453207add58004
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size 62837801
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data/vggface2_test.tar.gz
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version https://git-lfs.github.com/spec/v1
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size 2028325313
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data/vggface2_train.tar.gz
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version https://git-lfs.github.com/spec/v1
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size 37909212476
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meta/bb_landmark.tar.gz
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version https://git-lfs.github.com/spec/v1
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oid sha256:7d5c68eaf56c6f7f93910fc88da7d2b0fd61e77848b9c9c4dba6b78cdad2db11
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size 178409916
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meta/class_overlap_vgg1_2.txt
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VGGFace2 VGGFace
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n000004 n00000001
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n000006 n00000002
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n000061 n00000028
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n000081 n00000032
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n001333 n00000282
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n001459 n00001297
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n001479 n00000315
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n001967 n00000469
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n002002 n00000479
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n002285 n00000584
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n002332 n00000932
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n002464 n00002255
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n002724 n00000222
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n002744 n00000703
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n003177 n00000786
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n008455 n00002435
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n009017 n00002235
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meta/identity_meta.csv
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meta/test_agetemp_imglist.txt
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| 1 |
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|
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|
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|
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|
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|
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|
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|
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|
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|
meta/test_list.txt
ADDED
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|
meta/test_posetemp_imglist.txt
ADDED
|
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|
|
meta/train_list.txt
ADDED
|
@@ -0,0 +1,3 @@
|
|
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|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:f0adf062077543c894ca91a70324454ba6a151c4ac1aec8a2b453207add58004
|
| 3 |
+
size 62837801
|
samples_0.png
ADDED
|
Git LFS Details
|