我爱计算机视觉 标星,更快获取CVML新技术
CV君今天盘点了 CVPR 2019 所有人脸相关论文,总计51篇,其中研究人脸重建与识别的论文最多,人脸识别中新Loss的设计有好几篇, 人脸表情分析也不少, 检测和对齐相对很少了。
这些论文有较大数量都来自工业界,一些很实用的技术被提出来,比如有趣的人脸编辑和老化。
可以在以下网站下载这些论文:
http://openaccess.thecvf.com/CVPR2019.py
如果想要下载所有CVPR 2019论文,请点击这里:
重磅!CVPR 2019 论文终于全面开放下载!附百度云链接
人脸反欺诈、人脸识别对抗攻击
大规模人脸反欺诈、活体检测库,中科院、京东等
A Dataset and Benchmark for Large-Scale Multi-Modal Face Anti-Spoofing
Shifeng Zhang, Xiaobo Wang, Ajian Liu, Chenxu Zhao, Jun Wan, Sergio Escalera, Hailin Shi, Zezheng Wang, Stan Z. Li
深度树学习,用于零样本的人脸反欺诈,密歇根州立大学
Deep Tree Learning for Zero-Shot Face Anti-Spoofing
Yaojie Liu, Joel Stehouwer, Amin Jourabloo, Xiaoming Liu
去相关的对抗学习,用于年龄不变的人脸识别,腾讯
Decorrelated Adversarial Learning for Age-Invariant Face Recognition
Hao Wang, Dihong Gong, Zhifeng Li, Wei Liu
人脸识别对抗攻击,香港浸会大学
Multi-Adversarial Discriminative Deep Domain Generalization for Face Presentation Attack Detection
Rui Shao, Xiangyuan Lan, Jiawei Li, Pong C. Yuen
人脸识别对抗攻击,清华、腾讯、港理工
Efficient Decision-Based Black-Box Adversarial Attacks on Face Recognition
Yinpeng Dong, Hang Su, Baoyuan Wu, Zhifeng Li, Wei Liu, Tong Zhang, Jun Zhu
人脸重建与生成
多视图3D人脸变形模型回归,腾讯、香港中文、上交、电子科大
MVF-Net: Multi-View 3D Face Morphable Model Regression
Fanzi Wu, Linchao Bao, Yajing Chen, Yonggen Ling, Yibing Song, Songnan Li, King Ngi Ngan, Wei Liu
2500fps的3D人脸解码,3DMM(3D变形模型),帝国理工等
Dense 3D Face Decoding Over 2500FPS: Joint Texture & Shape Convolutional Mesh Decoders
Yuxiang Zhou, Jiankang Deng, Irene Kotsia, Stefanos Zafeiriou
GAN 用于3D 人脸重建,帝国理工等
GANFIT: Generative Adversarial Network Fitting for High Fidelity 3D Face Reconstruction
Baris Gecer, Stylianos Ploumpis, Irene Kotsia, Stefanos Zafeiriou
3DMM(3D变形模型),密歇根州立大学
Towards High-Fidelity Nonlinear 3D Face Morphable Model
Luan Tran, Feng Liu, Xiaoming Liu
3DMM(3D变形模型),帝国理工等
Combining 3D Morphable Models: A Large Scale Face-And-Head Model
Stylianos Ploumpis, Haoyang Wang, Nick Pears, William A. P. Smith, Stefanos Zafeiriou
3D人脸形状的解偶表示学习,中国科技大学
Disentangled Representation Learning for 3D Face Shape
Zi-Hang Jiang, Qianyi Wu, Keyu Chen, Juyong Zhang
单目人脸3D重建、跟踪与动画驱动,明尼苏达大学、Facebook
Self-Supervised Adaptation of High-Fidelity Face Models for Monocular Performance Tracking
Jae Shin Yoon, Takaaki Shiratori, Shoou-I Yu, Hyun Soo Park
多度量回归网络,用于非限制的人脸重建,北大、腾讯
MMFace: A Multi-Metric Regression Network for Unconstrained Face Reconstruction
Hongwei Yi, Chen Li, Qiong Cao, Xiaoyong Shen, Sheng Li, Guoping Wang, Yu-Wing Tai
单图像重建3D人脸形状和表情,德国马普研究所
Learning to Regress 3D Face Shape and Expression From an Image Without 3D Supervision
Soubhik Sanyal, Timo Bolkart, Haiwen Feng, Michael J. Black
密集3D人脸对应,中科院,Visytem公司
Boosting Local Shape Matching for Dense 3D Face Correspondence
Zhenfeng Fan, Xiyuan Hu, Chen Chen, Silong Peng
从视频中人脸模型和人脸3D重建的联合学习,MPI Informatics等
FML: Face Model Learning From Videos
Ayush Tewari, Florian Bernard, Pablo Garrido, Gaurav Bharaj, Mohamed Elgharib, Hans-Peter Seidel, Patrick Perez, Michael Zollhofer, Christian Theobalt
使用动态像素级Loss,层次跨模态说话人脸生成,罗彻斯特大学
Hierarchical Cross-Modal Talking Face Generation With Dynamic Pixel-Wise Loss
Lele Chen, Ross K. Maddox, Zhiyao Duan, Chenliang Xu
通过语音重建人脸,MIT
Speech2Face: Learning the Face Behind a Voice
Tae-Hyun Oh, Tali Dekel, Changil Kim, Inbar Mosseri, William T. Freeman, Michael Rubinstein, Wojciech Matusik
人脸聚类
图卷积人脸聚类,清华、澳大利亚国立大学
Linkage Based Face Clustering via Graph Convolution Network
Zhongdao Wang, Liang Zheng, Yali Li, Shengjin Wang
图卷积人脸聚类,商汤、港中文、南洋理工
Learning to Cluster Faces on an Affinity Graph
Lei Yang, Xiaohang Zhan, Dapeng Chen, Junjie Yan, Chen Change Loy, Dahua Lin
人脸识别
长尾噪声数据的不平等训练,用于深度人脸识别,北邮、佳能
Unequal-Training for Deep Face Recognition With Long-Tailed Noisy Data
Yaoyao Zhong, Weihong Deng, Mei Wang, Jiani Hu, Jianteng Peng, Xunqiang Tao, Yaohai Huang
Exclusive正则化的人脸识别,南开大学
RegularFace: Deep Face Recognition via Exclusive Regularization
Kai Zhao, Jingyi Xu, Ming-Ming Cheng
深度分布表示,用于人脸识别,清华
UniformFace: Learning Deep Equidistributed Representation for Face Recognition
Yueqi Duan, Jiwen Lu, Jie Zhou
ArcFace Loss,人脸识别,帝国理工
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
Jiankang Deng, Jia Guo, Niannan Xue, Stefanos Zafeiriou
梯度提精的人脸识别Loss,商汤、港中文、深圳高等技术研究院
P2SGrad: Refined Gradients for Optimizing Deep Face Models
Xiao Zhang, Rui Zhao, Junjie Yan, Mengya Gao, Yu Qiao, Xiaogang Wang, Hongsheng Li
人脸识别Loss AdaptiveFace,中科院、中科院大学、澳门科技大学
AdaptiveFace: Adaptive Margin and Sampling for Face Recognition
Hao Liu, Xiangyu Zhu, Zhen Lei, Stan Z. Li
人脸识别新Loss AdaCos,商汤、港中文、深圳高等技术研究所
AdaCos: Adaptively Scaling Cosine Logits for Effectively Learning Deep Face Representations
Xiao Zhang, Rui Zhao, Yu Qiao, Xiaogang Wang, Hongsheng Li
低秩拉普拉斯均匀混合模型,用于鲁棒人脸识别,中山大学
Low-Rank Laplacian-Uniform Mixed Model for Robust Face Recognition
Jiayu Dong, Huicheng Zheng, Lina Lian
抗噪人脸识别训练,北京化工大学、Yunshitu Corporation
Noise-Tolerant Paradigm for Training Face Recognition CNNs
Wei Hu, Yangyu Huang, Fan Zhang, Ruirui Li
人脸识别特征变换学习,密歇根州立大学、NEC、加利福尼亚大学
Feature Transfer Learning for Face Recognition With Under-Represented Data
Xi Yin, Xiang Yu, Kihyuk Sohn, Xiaoming Liu, Manmohan Chandraker
低质量3D 人脸识别的轻量级高效方法,北航、Anyvision
Led3D: A Lightweight and Efficient Deep Approach to Recognizing Low-Quality 3D Faces
Guodong Mu, Di Huang, Guosheng Hu, Jia Sun, Yunhong Wang
面向极端姿态与表情的非监督人脸归一化,用于人脸识别预处理,北邮、滴滴
Unsupervised Face Normalization With Extreme Pose and Expression in the Wild
Yichen Qian, Weihong Deng, Jiani Hu
跨模态人脸识别,商汤
R3 Adversarial Network for Cross Model Face Recognition
Ken Chen, Yichao Wu, Haoyu Qin, Ding Liang, Xuebo Liu, Junjie Yan
人脸检测
组采样用于尺度不变的人脸检测,西安交大、微软亚研院
Group Sampling for Scale Invariant Face Detection
Xiang Ming, Fangyun Wei, Ting Zhang, Dong Chen, Fang Wen
人脸检测,南京理工、腾讯
DSFD: Dual Shot Face Detector
Jian Li, Yabiao Wang, Changan Wang, Ying Tai, Jianjun Qian, Jian Yang, Chengjie Wang, Jilin Li, Feiyue Huang
人脸检测,马里兰大学
FA-RPN: Floating Region Proposals for Face Detection
Mahyar Najibi, Bharat Singh, Larry S. Davis
多人的联合人脸检测与人脸运动重定向,华盛顿大学、微软
Joint Face Detection and Facial Motion Retargeting for Multiple Faces
Bindita Chaudhuri, Noranart Vesdapunt, Baoyuan Wang
表情分析与人脸动作单元检测
联合表示与估计学习,用于人脸动作单元强度估计,腾讯、中科院模式识别国家实验室、伦斯勒理工学院
Joint Representation and Estimator Learning for Facial Action Unit Intensity Estimation
Yong Zhang, Baoyuan Wu, Weiming Dong, Zhifeng Li, Wei Liu, Bao-Gang Hu, Qiang Ji
人脸动作检测、中科院等
Local Relationship Learning With Person-Specific Shape Regularization for Facial Action Unit Detection
Xuesong Niu, Hu Han, Songfan Yang, Yan Huang, Shiguang Shan
人脸表情相似性的紧凑嵌入,人脸表情分析新范式,Google
A Compact Embedding for Facial Expression Similarity
Raviteja Vemulapalli, Aseem Agarwala
视频中自监督表示学习用于人脸动作检测,中科院、鹏城实验室
Self-Supervised Representation Learning From Videos for Facial Action Unit Detection
Yong Li, Jiabei Zeng, Shiguang Shan, Xilin Chen
人脸对齐
语义对齐,用于人脸特征点检测,中科院自动化所
Semantic Alignment: Finding Semantically Consistent Ground-Truth for Facial Landmark Detection
Zhiwei Liu, Xiangyu Zhu, Guosheng Hu, Haiyun Guo, Ming Tang, Zhen Lei, Neil M. Robertson, Jinqiao Wang
遮挡自适应的深度网络,用于鲁棒人脸特征点检测,深圳大学
Robust Facial Landmark Detection via Occlusion-Adaptive Deep Networks
Meilu Zhu, Daming Shi, Mingjie Zheng, Muhammad Sadiq
人脸编辑
3D引导的细粒度人脸编辑,斯坦福大学、Snap
3D Guided Fine-Grained Face Manipulation
Zhenglin Geng, Chen Cao, Sergey Tulyakov
语义部件分解,用于人脸属性编辑,港中文、腾讯、Adobe、字节跳动
Semantic Component Decomposition for Face Attribute Manipulation
Ying-Cong Chen, Xiaohui Shen, Zhe Lin, Xin Lu, I-Ming Pao, Jiaya Jia
人脸老化
视频人脸老化,基于深度强化学习,使得老化后的人脸在视频中更具一致性,康考迪亚大学、阿肯色大学、克莱姆森大学、卡内基梅隆大学
Automatic Face Aging in Videos via Deep Reinforcement Learning
Chi Nhan Duong, Khoa Luu, Kha Gia Quach, Nghia Nguyen, Eric Patterson, Tien D. Bui, Ngan Le
基于小波的GAN,用于属性感知的人脸老化,中科院
Attribute-Aware Face Aging With Wavelet-Based Generative Adversarial Networks
Yunfan Liu, Qi Li, Zhenan Sun
人脸肖像化
层次化GANs,用于从人脸照片生成肖像画,清华、英国Cardiff University
APDrawingGAN: Generating Artistic Portrait Drawings From Face Photos With Hierarchical GANs
Ran Yi, Yong-Jin Liu, Yu-Kun Lai, Paul L. Rosin
人脸采集 Face Capture
高质量人脸采集,使用肌肉解剖模型,斯坦福大学、Industrial Light & Magic
High-Quality Face Capture Using Anatomical Muscles
Michael Bao, Matthew Cong, Stephane Grabli, Ronald Fedkiw
单目人脸、肢体、手部动作采集,卡内基梅隆大学
Monocular Total Capture: Posing Face, Body, and Hands in the Wild
Donglai Xiang, Hanbyul Joo, Yaser Sheikh
单图像的3D手部、人脸、肢体采集,MPI
Expressive Body Capture: 3D Hands, Face, and Body From a Single Image
Georgios Pavlakos, Vasileios Choutas, Nima Ghorbani, Timo Bolkart, Ahmed A. A. Osman, Dimitrios Tzionas, Michael J. Black
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超级连接者:破解新互联时代的成功密码
伊桑•祖克曼(ETHAN ZUCKERMAN) / 林玮、张晨 / 浙江人民出版社 / 2018-8-1 / CNY 72.90
● 我们生活在一个互联互通的世界,我们需要辩证地看待某些事件,发现隐藏在背后的真相。着眼当下,看清彼此之间的联系,而非凭空幻想未来世界联系之紧密。数字世界主义要求我们承担起责任,让隐藏的联系变成现实。 ● 我们对世界的看法是局限的、不完整的、带有偏见的。如果我们想要改变从这个广阔的世界所获取的信息,我们需要做出结构性的改变。 ● 建立联系是一种新的力量。无论是在国家层面、企业层面还是个......一起来看看 《超级连接者:破解新互联时代的成功密码》 这本书的介绍吧!