When benchmarking an algorithm it is recommendable to use a standard
test data set for researchers to be able to directly compare the
results. While there are many databases in use currently, the choice of
an appropriate database to be used should be made based on the task
given (aging, expressions, lighting etc). Another way is to choose the
data set specific to the property to be tested (e.g. how algorithm
behaves when given images with lighting changes or images with
different facial expressions).
- 3D_RMA database
- AMP-CMU
- AR (Aleix)
- AT&T
- BANCA
- BFM
- BioID
- BJUT-3D
- Bosphorus 3D Database
- CALTECH
- CASIA Face Image Database
- CAS-PEAL
- CMU Cohn-Kanade AU
- CMU PIE
- CMU VASC
- CVL
- EQUINOX HID
- ESSEX
- FERET
- FG-NET Aging
- FG-NET Talking face
- FRAV2D
- FRAV3D
- FRGC
- GavabDB
- Georgia Tech
- ICPR
- Image Database of Facial Actions and Expressions
- Indian Face Database
- JAFFE
- Labeled Faces in the Wild
- LFW
- MAX PLANCK
- MIT-CBCL
- MIT-CSAIL
- NIST MID
- NLPR
- OULU
- PICS
- SCface
- UCFI (UCD)
- VALID
- VidTIMIT
- VIOLA training set
- WEIZMANN
- XM2VTS
- YALE A
- YALE B
Index Terms: face, database, databases, download, list.
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Figure 1. Face database |
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A complete list of public face databases available on the web. Last update: 22 Feb. 2011. |
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