About This Special Issue

Deep learning is one of the most important breakthroughs in the field of artificial intelligence over the last decade. It has achieved great success in speech recognition, natural language processing, computer vision, and multimedia. Many face analysis tasks, including face detection, alignment, reconstruction, and recognition, benefit from the powerful representation learning capability of deep learning techniques. Not only there has been a constantly growing flow of related research papers, but also substantial progress has been achieved in real-world applications such as security, video surveillance, and human-computer interaction.

While substantial progress has been achieved in face analysis with deep learning, many issues still remain and new problems emerge. For instance, the scalability of deep networks to large-scale unconstrained recognition needs be improved. In-the-wild facial attributes recognition with imbalance class distribution is still challenging. The accuracy and efficiency of detecting faces with a wide range of scales in a crowded scene still see a large room for improvement.

This special issue presents a great platform to make a definitive statement about the state of the art by providing a significant collective contribution to this emerging field of study.

International Journal of Computer Vision
Volume 127, Issues 6-7 Pages 533-971 (June 2019)
Deep Learning for Face Analysis
Edited by Chen Change Loy, Xiaoming Liu, Tae-Kyun Kim, Fernando De la Torre, Rama Chellappa

Access

The issue is available electronically on Springer at the following link: https://link.springer.com/journal/11263/127/6

Table of Contents

  1. Editorial: Special Issue on Deep Learning for Face Analysis
    Chen Change Loy, Xiaoming Liu, Tae-Kyun Kim, Fernando De la Torre, Rama Chellappa
    PDF

  2. Single-Shot Scale-Aware Network for Real-Time Face Detection
    Shifeng Zhang, Longyin Wen, Hailin Shi, Zhen Lei, Siwei Lyu, and Stan Z. Li

  3. Hierarchical Attention for Part-Aware Face Detection
    Shuzhe Wu, Meina Kan, Shiguang Shan, and Xilin Chen

  4. Real-Time 3D Head Pose Tracking Through 2.5D Constrained Local Models with Local Neural Fields
    Stephen Ackland, Francisco Chiclana, Howell Istance, and Simon Coupland

  5. The Menpo Benchmark for Multi-pose 2D and 3D Facial Land- mark Localisation and Tracking
    Jiankang Deng, Anastasios Roussos, Grigorios Chrysos, Evangelos Ververas, Irene Kotsia, Jie Shen, and Stefanos Zafeiriou

  6. Face Mask Extraction in Video Sequence
    Yujiang Wang, Bingnan Luo, Jie Shen, and Maja Pantic

  7. Face-Specific Data Augmentation for Unconstrained Face Recognition
    Iacopo Masi, Anh Tuấn Trần, Tal Hassner, Gozde Sahin, and Gérard Medioni

  8. A Comprehensive Study on Center Loss for Deep Face Recognition
    Yandong Wen, Kaipeng Zhang, Zhifeng Li, and Yu Qiao

  9. Large-scale Bisample Learning on ID vs. Spot Face Recognition
    Xiangyu Zhu, Hao Liu, Zhen Lei, Hailin Shi, Fan Yang, Dong Yi, Guojun Qi, and Stan Z. Li

  10. Learning Discriminative Aggregation Network for Video-based Face Recognition and Person Re-identification
    Yongming Rao, Jiwen Lu, and Jie Zhou

  11. Detecting and Mitigating Adversarial Perturbations for Robust Face Recognition
    Gaurav Goswami, Akshay Agarwal, Nalini Ratha, Richa Singh, and Mayank Vatsa

  12. An Adversarial Neuro-Tensorial Approach For Learning Disentangled Representations
    Mengjiao Wang, Zhixin Shu, Shiyang Cheng, Yannis Panagakis, Dimitris Samaras, and Stefanos Zafeiriou

  13. Wavelet Domain Generative Adversarial Network for Multi-scale Face Hallucination
    Huaibo Huang, Ran He, Zhenan Sun, and Tieniu Tan

  14. Joint Face Hallucination and Deblurring via Facial Structure Generation and Detail Enhancement
    Yibing Song, Jiawei Zhang, Lijun Gong, Shengfeng He, Linchao Bao, Jin- shan Pan, Qingxiong Yang, and Ming-Hsuan Yang

  15. Motion Deblurring of Faces
    Grigorios G. Chrysos, Paolo Favaro, and Stefanos Zafeiriou

  16. Disentangling Geometry and Appearance with Geometry-Aware Generative Adversarial Network
    Linh Tran, Jean Kossaifi, Yannis Panagakis, and Maja Pantic

  17. Synthesis of High-Quality Visible Faces from Polarimetric Thermal Faces using Generative Adversarial Networks
    He Zhang, Benjamin S. Riggan, Shuowen Hu, Nathaniel J. Short, and Vishal M. Patel

  18. Face Recovery from Stylized Portraits
    Fatemeh Shiri, Xin Yu, Fatih Porikli, Richard Hartley, and Piotr Koniusz

  19. Blended Emotion in-the-Wild: Multi-label Facial Expression Recognition Using Crowdsourced Annotations and Deep Locality Fea- ture Learning
    Shan Li and Weihong Deng

  20. Deep Affect Prediction in-the-wild: Aff-Wild Database and Challenge, Deep Architectures, and Beyond
    Dimitrios Kollias, Panagiotis Tzirakis, Mihalis A. Nicolaou, Athanasios Papaioannou, Guoying Zhao, Bjo ̈rn Schuller, Irene Kotsia, and Stefanos Zafeiriou

  21. Deep, Landmark-Free FAME: Face Alignment, Modeling, and Expression Estimation
    Feng-Ju Chang, Anh Tuan Tran, Tal Hassner, Iacopo Masi, Ram Nevatia, and Gerard Medioni

  22. Learning from Longitudinal Face Demonstration - Where Tractable Deep Modeling Meets Inverse Reinforcement Learning
    Chi Nhan Duong, Kha Gia Quach, Khoa Luu, T. Hoang Ngan Le, Marios Savvides, and Tien D. Bui

Guest Editors

Rama Chellappa, University of Maryland, USA
Xiaoming Liu, Michigan State University, USA
Tae-Kyun Kim, Imperial College London, UK
Fernando De la Torre, Facebook, USA
Chen Change Loy, Nanyang Technological University, Singapore