Morph Ii Dataset · Latest & Confirmed

| Dataset | Images | Subjects | Longitudinal? | Primary Weakness | | :--- | :--- | :--- | :--- | :--- | | | 55k | 13.6k | Yes | Demographic skew | | FG-NET | 1,002 | 82 | Yes | Very small size | | UTKFace | 20k | ~20k | No | Cross-sectional only | | IMDB-WIKI | 523k | 20k | No | Noisy labels, no longitudinal pairs | | CACD (Cross-Age) | 16k | 2k | Yes | Small subject count |

In the rapidly evolving fields of computer vision, biometrics, and forensic science, data is the new oil. However, not all data is created equal. While many datasets offer thousands of static images of different people, few provide the temporal depth required to study how a human face changes over years or even decades. Enter the MORPH II dataset —a cornerstone resource for researchers studying age progression, age estimation, and facial recognition across time. morph ii dataset

The "II" signifies that it is the second major release of the MORPH database. The original MORPH (Album 1) contained approximately 1,300 subjects. MORPH II expanded this dramatically to become, for many years, the largest publicly available dataset for studying facial aging. | Dataset | Images | Subjects | Longitudinal

If you are working on age-invariant face recognition or developing algorithms to predict chronological age from a single photograph, you have likely encountered the name MORPH II. But what makes this dataset so special? Why has it become a benchmark standard since its release? This article provides an exhaustive deep dive into the MORPH II dataset, its structure, its applications, and its limitations. The MORPH II dataset (often stylized as MORPH Album 2) is a large-scale, longitudinal facial image database compiled by the University of North Carolina Wilmington (UNCW) in collaboration with the National Institute of Justice (NIJ). Unlike standard datasets that collect one image per subject, MORPH II focuses on temporal variation . While many datasets offer thousands of static images

As of 2023-2025, the original hosting at UNCW has become less active, and the dataset is most reliably accessed via the National Institute of Standards and Technology (NIST) and face recognition research communities.