Face Image
Face image analysis is a rapidly evolving field focused on developing robust and accurate methods for processing and understanding facial images. Current research emphasizes improving the quality of face images through techniques like super-resolution and restoration, enhancing the interpretability of face recognition systems using natural language processing and explainable AI, and mitigating biases in both face recognition and generation models. These advancements have significant implications for various applications, including security, healthcare, and social sciences, by improving the accuracy and fairness of facial analysis technologies.
Papers
Sampling Strategies for Mitigating Bias in Face Synthesis Methods
Emmanouil Maragkoudakis, Symeon Papadopoulos, Iraklis Varlamis, Christos Diou
Testing the Performance of Face Recognition for People with Down Syndrome
Christian Rathgeb, Mathias Ibsen, Denise Hartmann, Simon Hradetzky, Berglind Ólafsdóttir
SecurePose: Automated Face Blurring and Human Movement Kinematics Extraction from Videos Recorded in Clinical Settings
Rishabh Bajpai, Bhooma Aravamuthan
Real-time 3D-aware Portrait Editing from a Single Image
Qingyan Bai, Zifan Shi, Yinghao Xu, Hao Ouyang, Qiuyu Wang, Ceyuan Yang, Xuan Wang, Gordon Wetzstein, Yujun Shen, Qifeng Chen