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
FaceOracle: Chat with a Face Image Oracle
Wassim Kabbani, Kiran Raja, Raghavendra Ramachandra, Christoph Busch
Radial Distortion in Face Images: Detection and Impact
Wassim Kabbani, Tristan Le Pessot, Kiran Raja, Raghavendra Ramachandra, Christoph Busch
Eye Sclera for Fair Face Image Quality Assessment
Wassim Kabbani, Kiran Raja, Raghavendra Ramachandra, Christoph Busch
FaceX: Understanding Face Attribute Classifiers through Summary Model Explanations
Ioannis Sarridis, Christos Koutlis, Symeon Papadopoulos, Christos Diou
Learning Spatially Decoupled Color Representations for Facial Image Colorization
Hangyan Zhu, Ming Liu, Chao Zhou, Zifei Yan, Kuanquan Wang, Wangmeng Zuo