A face’s memorability refers to the unique combination of its intrinsic visual features facilitating its later recognition. Despite considerable variation in face recognition ability amongst the general population, individuals show substantial concordance regarding the memorability of various faces. And, when the viewpoints across which identities are seen at encoding and recognition differ, such agreement persists, though to a lesser extent. Consequently, face recognition cannot rely solely on image-dependent encoding; individuals must extract some invariant facial information, robust to changes in viewpoint, to do so consistently. However, whether such consistency covaries with overall face processing ability is unclear. Here, therefore, in two experiments we tested recognition of (i) implicitly encoded face images and (ii) explicitly encoded identities in a group of normal control observers against a group of “Super-Recognizers” (SRs) who possess exceptional face processing skills. When implicit encoding was surreptitiously solicited, recognition of studied images was comparable between groups. Yet, when encoding was explicitly solicited, SRs more accurately recognized studied identities across viewpoint changes than normal observers. Critically, image-dependent information could only inform recognition in the first experiment, whereas viewpoint-invariant information could inform recognition consistently in both. Individualized profiles of observers’ performance (as a function of stimulus memorability) reveal that only SRs performed consistently between experiments. We suggest that SRs’ unique capacity for utilizing viewpoint-invariant information for recognition, regardless of encoding conditions, is rooted in fundamentally more accurate and robust representations of identity-based memorability. These results invite a reinterpretation of face memorability that describes viewpoint-invariant information, diagnostic of facial identity representations in memory.

Facial identity matching ability varies widely, ranging from severely deficient prosopagnosics (who exhibit profound impairments in face cognition) to so-called Super-Recognizers (SRs), possessing exceptional capacities for processing facial identity. Yet, despite the often consequential nature of face matching decisions—such as identity verification in security critical settings—ability assessments rely on simple performance metrics on a handful of heterogeneously related subprocesses, or in some cases only a single measured subprocess. Unfortunately, methodologies of this ilk leave contributions of stimulus information to observed variations in ability largely unspecified. Moreover, they are inadequate for addressing the qualitative or quantitative nature of differences between SRs’ abilities and those of the general population. Here, therefore, we sought to investigate individual differences—among SRs identified using a novel conservative diagnostic framework, and neurotypical controls—by systematically varying retinal availability, bandwidth, and orientation of faces’ spatial frequency content over two face matching experiments. Psychophysical evaluations of these parameters’ contributions to ability reveal that SRs more consistently exploit the same spatial frequency information, rather than suggesting qualitatively different profiles between normal observers and SRs. These findings stress the importance of optimizing procedures for SR diagnosis to include measures of individuals’ consistency.

When you hear the word Super-Recognizer, you may think of comic-book-hero-esque agents searching the underground to find people who went missing decades ago. Compared to this fantasy, the reality seems somewhat less exciting. Super-Recognizers (SRs) were initially reported a decade ago as a collateral while developing tests for developmental prosopagnosia. Today, the topic of SRs sparks interest from groups seeking to enhance scientific knowledge, public safety, or their monetary gain. With no immediate consequences of erroneous SR identification, there has been no pressure to establish a clear SR definition. This promotes heterogenous empirical evidence and the proliferation of unsupported claims in the media. Not only is this status quo unfortunate, it stands in opposition to the potential of special populations – both for science and application. SRs are a special population with imminent real-world value that can advance our understanding of brain functioning. To exploit their potential, I propose a needed formal framework for SR diagnosis, and introduce 70 cases identified based hereupon. These cases represent the core of a growing SR cohort, studied in my lab in the course of a long-term, multi-methodological research agenda involving academic and government collaborators. Finally, I provide recommendations for those interested in SR work, and highlight current caveats and future challenges.

Recognizing individuals based on their face represents a critical component of police work – from identity checks to image intelligence. This capacity, which is at best trainable to a limited extent, varies from person to person and represents one of the greatest challenges for the human brain. In particular processing of unfamiliar faces is extremely error-prone. At the same time, the demand for this task is steadily increasing due to increasing availability of video and image material. To address this, some police agencies are interested in deploying so-called Super-Recognizers: individuals who have a natural propensity for processing faces, and who do so extremely proficiently without any form of training. Super-Recognizers were first scientifically introduced in 2009 – their future lies in the collaboration between police and scientific research.

[Personen anhand ihres Gesichts zu erkennen, stellt einen wesentlichen Bestandteil der polizeilichen Arbeit dar – von der Personenkontrolle bis hin zur Bildfahndung. Diese Fähigkeit, die sich nur bedingt trainieren lässt, variiert von Person zu Person und ist eine der herausforderndsten Aufgaben für das menschliche Gehirn. Vor allem die Verarbeitung unbekannter Gesichter ist extrem fehleranfällig. Gleichzeitig ist dies eine Aufgabe, die aufgrund der Zunahme an zu bearbeitendem Video- und Bildmaterial stetig wächst. Um dieser Situation gerecht zu werden, setzen einige Behörden deshalb auf sogenannte Super-Recognizer: Personen, die von Natur aus und ohne Training Gesichter extrem gut verarbeiten und wiedererkennen können. Super-Recognizer wurden von der Wissenschaft erstmals 2009 thematisiert – die Zukunft liegt in der Zusammenarbeit zwischen Polizei und Forschung.]

Rossion et al. (2020) review over a decade of work investigating the neural basis of unfamiliar face individuation (FI)—the brain's ability to distinguish unfamiliar face identity—using fast periodic visual stimulation (FPVS). Though FPVS measures rapid, automatic processing, its value for studying vision and face cognition could be increased by addressing three important aspects.

Recent investigations of individual differences have demonstrated striking variability in performance both within the same subprocess in face cognition (e.g. face perception), but also between two different subprocesses (i.e. face perception versus face recognition) that are assessed using different tasks (face matching versus face memory). Such differences between and within individuals between and within laboratory tests raise practical challenges. This applies in particular to the development of screening tests for the selection of personnel in real-world settings where faces are routinely processed, such as at passport control. The aim of this study, therefore, was to examine the performance profiles of individuals within and across two different subprocesses of face cognition: face perception and face recognition. To this end, 146 individuals completed four different tests of face matching—one novel tool for assessing proficiency in face perception, as well as three established measures—and two benchmark tests of face memory probing face recognition. In addition to correlational analyses, we further scrutinized individual performance profiles of the highest and lowest performing observers identified per test, as well as across all tests. Overall, a number of correlations emerged between tests. However, there was limited evidence at the individual level to suggest that high proficiency in one test generalized to other tests measuring the same subprocess, as well as those that measured a different subprocess. Beyond emphasizing the need to honour inter-individual differences through careful multivariate assessment in the laboratory, our findings have real-world implications: combinations of tests that most accurately map the task(s) and processes of interest are required for personnel selection.

Unfamiliar face processing is an ability that varies considerably between individuals. Numerous studies have aimed to identify its underlying determinants using controlled experimental procedures. While such tests can isolate variables that influence face processing, they usually involve somewhat unrealistic situations and optimized face images as stimulus material. As a consequence, the extent to which the performance observed under laboratory settings is informative for predicting real-life proficiency remains unclear. We present normative data for two ecologically valid but underused tests of face matching: the Yearbook Test (YBT) and the Facial Identity Card Sorting Test (FICST). The YBT (n = 252) measures identity matching across substantial age-related changes in facial appearance, while the FICST (n = 218) assesses the ability to process unfamiliar facial identity despite superficial image variations. To determine the predictive value of both tests, a subsample of our cohort (n = 181) also completed a commonly used test of face recognition and two tests of face perception (the long form of the Cambridge Face Memory Test (CFMT+), the Expertise in Facial Comparison Test (EFCT) and the Person Identification Challenge Test (PICT)). Focusing on the top performers identified independently per test, we made two important observations: 1) YBT and FICST performance can predict CFMT+ scores and vice versa; and 2) EFCT and PICT scores neither reliably predict superior performance in ecologically meaningful and challenging tests of face matching, nor in the most commonly used test of face recognition. These findings emphasize the necessity for using challenging and ecologically relevant, and thus highly sensitive, tasks of unfamiliar face processing to identify high-performing individuals in the normal population.

This article provides a response to five excellent commentaries on our article ‘Super‐recognizers: From the lab to the world and back again’. Specifically, the response summarizes commonalities between these commentaries. Based on this consensus, we propose a flexible framework for the assessment of superior face recognition and outline guiding principles to advance future work in the field.

The recent discovery of individuals with superior face processing ability has sparked considerable interest amongst cognitive scientists and practitioners alike. These ‘Super‐recognizers’ (SRs) offer clues to the underlying processes responsible for high levels of face processing ability. It has been claimed that they can help make societies safer and fairer by improving accuracy of facial identity processing in real‐world tasks, for example when identifying suspects from Closed Circuit Television or performing security‐critical identity verification tasks. Here, we argue that the current understanding of superior face processing does not justify widespread interest in SR deployment: There are relatively few studies of SRs and no evidence that high accuracy on laboratory‐based tests translates directly to operational deployment. Using simulated data, we show that modest accuracy benefits can be expected from deploying SRs on the basis of ideally calibrated laboratory tests. Attaining more substantial benefits will require greater levels of communication and collaboration between psychologists and practitioners. We propose that translational and reverse‐translational approaches to knowledge development are critical to advance current understanding and to enable optimal deployment of SRs in society. Finally, we outline knowledge gaps that this approach can help address.