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...
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...
4. Dataset Collection 数据集建立的过程,对应一般 paper 的 method 部分。 一般包含几个阶段: 数据来源 具体的收集举措 去除噪声 5. Experiment 实验部分又是一个重点,关键在于说明自己数据集的优势。 收集人脸在不同 pose, age 下的照片,用以验证不同模型 pose/age invariant 的能力 在VGGFace2 和其他数据集上...
An implementation to clean large scale public face dataset graph-algorithmsface-recognitionface-datasetvggface2 UpdatedDec 12, 2019 Python Star4 Developed a deep novel coupled profile to frontal face recognition network incorporating pose as an auxiliary information via attention mechanism (i.e., impleme...
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: A dataset for recognising faces across pose and age. In FG, 2018.Q. Cao, L. Shen, W. Xie, O. M. Parkhi, and A. Zisserman. VGGFace2: A dataset for recognising faces across pose and age. In Proc. Int. Conf. Autom. Face and Gesture Recog., 2018....
VGGFace2 Dataset for Face Recognition (website) The dataset contains 3.31 million images of 9131 subjects (identities), with an average of 362.6 images for each subject. Images are downloaded from Google Image Search and have large variations in pose, age, illumination, ethnicity and profession (...
In this paper, we introduce a new large-scale face dataset named VGGFace2. The dataset contains 3.31 million images of 9131 subjects, with an average of 362.6 images for each subject. Images are downloaded from Google Image Search and have large variations in pose, age, illumination, ethnicity...
This repo implements training and testing models, and feature extractor based on models for VGGFace2 [1]. Pretrained modelsfor PyTorch are converted fromCaffe modelsauthors of [1] provide. Dataset To download VGGFace2 dataset, seeauthors' site. ...
这个模型是《Deep Learning高质量》群里的牛津大神Weidi Xie在介绍他们的VGG face2时候,看到对应的论文《VGGFace2: A dataset for recognising faces across pose and age》中对比实验涉及到的SENet,其结果比ResNet-50还好,所以也学习学习。 github上的SENet ...