2023/03/30 by Jerone T. A. Andrews, Andrews, Jerone T. A., Przemyslaw Joniak +3
Computer Science · Neuroscience · Psychology · #Computer Vision and Pattern Recognition (cs.CV) #Evolutionary Psychology and Human Behavior #FOS: Computer and information sciences #Face Recognition and Perception #Face recognition and analysis
paper · pdf · doi:10.48550/arxiv.2303.17176
openalex publication_date 2023/03/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Few datasets contain self-identified sensitive attributes, inferring attributes risks introducing additional biases, and collecting attributes can carry legal risks. Besides, categorical labels can fail to reflect the continuous nature of human phenotypic diversity, making it difficult to compare the similarity between same-labeled faces. To address these issues, we present A View From Somewhere (AVFS) -- a dataset of 638,180 human judgments of face similarity. We demonstrate the utility of AVFS for learning a continuous, low-dimensional embedding space aligned with human perception. Our embedding space, induced under a novel conditional framework, not only enables the accurate prediction of face similarity, but also provides a human-interpretable decomposition of the dimensions used in the human-decision making process, and the importance distinct annotators place on each dimension. We additionally show the practicality of the dimensions for collecting continuous attributes, performing classification, and comparing dataset attribute disparities.