AnyFace: A Data-Centric Approach For Input-Agnostic Face Detection

Abstract

Face detection is a mandatory step in many computer vision applications, such as face recognition, emotion recognition, age detection, virtual makeup, and vital sign monitoring. Thanks to advancements in deep learning and the introduction of annotated large-scale datasets, numerous applications have been developed for human faces. Recently, other domains, such as animals and cartoon characters, have started gaining attention but still lag far behind human faces. The biggest challenge is the limited number of annotated face datasets in these domains. The manual labeling of large-scale datasets is tedious and requires substantial human labor. In this regard, we present an inputagnostic face detector to ease the annotation of various face datasets. We propose a simple but effective data-centric approach instead of building a specific neural network architecture. Specifically, we trained a face detection model, YOLO5Face, on human, animal, and cartoon face datasets. The experiments show that the model can achieve accurate results in all domains. In addition, the model achieved decent results for animals and cartoon characters different from the ones in the training set. This implies that the model can extract agnostic facial features. We have made the source code and pre-trained models publicly available at https://github.com/IS2AI/AnyFace to stimulate research in these fields.

Towards Unlocking the Hidden Potentials of the Data-Centric AI Paradigm in the Modern Era

“…The DC-AI paradigm has already achieved breakthroughs in many AI applications such as reducing the time from the implementation to the deployment of AI models, training AI models with fewer data, accelerating the convergence of AI models, reducing the overall complexity of AI models, reducing the cost of AI technology by exploiting the code of already-developed models, and extending AI applications [59][60][61][62][63]. The umbrella of DC-AI applications and techniques is constantly expanding, and therefore, the adoption of AI technology is increasing worldwide.…”