III.VGGFACE2的概述 A.Dataset统计 VGGFace2数据集包含来自9131名名人的330万张图片,这些名人跨越多种族,例如它包括比VGGFace更多的中国和印度面孔(尽管,种族平衡仍然受到名人和公众人物分布的限制)和职业(例如政治家和运动员)。图像是从谷歌图像搜索下载的,并显示姿势,年龄,灯光和背景的大变化。该数据集大致具有性别...
2. Dataset Review 3. Overview of VGGFace2 4. Dataset Collection 5. Experiment 我最近在做一个数据集相关的工作,写论文的时候发现自己不太了解这类文章的结构。因此梳理一下 VGGFace2 这篇数据集论文的结构。 VGGFace2 Websitewww.robots.ox.ac.uk/~vgg/data/vgg_face2/ VGGFace2 Paperwww.robots...
VGGface2是一个能够用于识别不同姿态和年龄人脸的数据集,数据集包含了440028张有效图片,数据集内人脸数据已经对齐 - 飞桨AI Studio
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。 VGGFace2 是一个大规模人脸识别数据,包含331万图片,9131个ID,平均图片个数为36...
VGGFace2 is a large-scale face recognition dataset. Images are downloaded from Google Image Search and have large variations in pose, age, illumination, ethnicity and profession. VGGFace2 contains images from identities spanning a wide range of different
Zisserman. Vggface2: A dataset for recognising faces across pose and age. In International Conference on Automatic Face and Gesture Recognition, 2018.Cao, Q., Shen, L., Xie, W., Parkhi, O.M., Zisserman, A.: Vggface2: A dataset for recognising faces across pose and age. In: Automatic...
VGGFace2: A dataset for recognising faces across pose and age, Q. Cao, L. Shen, W. Xie, O. M. Parkhi, A. Zisserman, In FG 2018. News DateUpdate 2018-10-01Models imported to PyTorch. Example scripts for cropping faces and evaluating on IJB-B can be found in the folder 'standard...
VGG-Face dataset, described in [2], is not planned to be supported in this repo. If you are interested in models for VGG-Face, seekeras-vggface. References ZQ. Cao, L. Shen, W. Xie, O. M. Parkhi, A. Zisserman, VGGFace2: A dataset for recognising faces across pose and age, 20...
be evaluated using the same type of image standardization. Hence, the flag--use_fixed_image_standardizationshould be used also for evaluation. 1% of the training images are used for validation. Since the amount of label noise in the VGGFace2 dataset is low no dataset filtering has been ...
The dataset was collected with three goals in mind: (i) to have both a large number of identities and also a large number of images for each identity; (ii) to cover a large range of pose, age and ethnicity; and (iii) to minimize the label noise. We describe how the dataset was ...