IIIT-Delhi Disguise Face Database


IIIT-Delhi Disguise Face Database is a dataset containing images pertaining to 75 subjects with different kinds of disguise variations. The version 1 of the dataset consists of images captured in visible spectrum. It is named as IIIT-Delhi Disguise Version 1 face database (ID V1). The IIITD In and Beyond Visible Spectrum Disguise database (I2BVSD)consists of face images captured in visible as well as thermal spectrum. Thus, ID V1 is a subset of I2BVSD.

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IIIT-D Kinect RGB-D Face Database


The IIIT-D RGB-D face database comprises of 106 male and female subjects with multiple RGB-D images of each subject. All the images are captured using a Microsoft Kinect sensor. The OpenNI API captures the RGB image and depth map as separate 24-bit images. Since the images are unsegmented, the database can be used for both face detection and recognition in RGB-D space. The number of images per subject are variable with a minimum of 11 images and a maximum of 254. The total number of images in the database is 4605 and the size of each image is 640x480.

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WhoIsIt (WIT) Face Database


IIIT-Delhi's WhoIsIt Database (WIT) contains images of 110 well known personalities, with at least 10 images per subject. The images aim to capture the age weight variation of the subjects over a period of time. The average age span per subject is 24.3 years. All the images have been downloaded from the internet and age has been estimated by the authors. The details of the database and performance of some well known face recognition algorithms is available in the paper mentioned below.

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Sketch Face Database


IIIT-Delhi sketch database consist of three different types of sketches, namely, viewed, semi-forensic, and forensic sketches. Each user in the database has a sketch and a corresponding digital photograph. It introduces semi-forensic sketches that are drawn based on the memory of sketch artist to act as an intermediate representation between viewed and forensic sketches.
For more details about the database, please visit here.

Disclaimer: This database consists of images collected from the internet. These forensic sketch-digital image pairs are collected in same spirit and understanding as the PubFig dataset and the Labeled Faces in the Wild (LFW) dataset. Therefore, we are sharing the direct link to the face images. Researchers can use this database but are not encouraged to publish any images from the database due to privacy reasons. Copyright of these images are with the original creators.

The database can be downloaded from the following link.
  • IIIT-D Sketch Database ReadMe
  • To obtain the password for the compressed file, kindly take a print out of the license agreement, fill it up and send the scanned copy to anushs@iiitd.ac.in. with the subject line "License agreement for IIIT-D Sketch Database".
    As soon as we obtain the signed license agreement in scanned form, we would provide you with the access to our database.
    NOTE: The license agreement has to be signed by faculty members or equivalent. It is not possible to accept license agreements signed by students and temporary researchers

    This database is available only for research and educational purpose and not for any commercial use. If you use the database in any publications or reports, you must refer to the following paper:
  • H.S. Bhatt, S. Bharadwaj, R. Singh, and M. Vatsa, Memetically Optimized MCWLD for Matching Sketches with Digital Face Images, IEEE Transactions on Information Forensics and Security, Vol. 5, No. 5, pp. 1522-1535, 2012.


  • Look Alike Face Database


    Look Alike face database consists of images pertaining to 50 well known personalities (from western, eastern, and asian origins) and their look-alikes. Each subject/class has five genuine images (total 505 genuine cases) and five look-alike images (total 505 look-alikes). To obtain the database, email the duly filled license agreement, to anushs@iiitd.ac.in with the subject line "License agreement for Look Alike Face Database".
    NOTE: The license agreement has to be signed by faculty members or equivalent. It is not possible to accept license agreements signed by students and temporary researchers

    This database is available only for research and educational purpose and not for any commercial use. If you use the database in any publications or reports, you must refer to the following paper:
  • H. Lamba, A. Sarkar, M. Vatsa, and R. Singh, Face Recognition for Look-Alikes: A Preliminary Study, In Proceedings of International Joint Conference on Biometrics, 2011.



  • Plastic Surgery Face Database


    The plastic surgery face database is a real world database that contains 1800 pre and post surgery images pertaining to 900 subjects. For each individual, there are two frontal face images with proper illumination and neutral expression: the first is taken before surgery and the second is taken after surgery. The database contains 519 image pairs corresponding to local surgeries and 381 cases of global surgery (e.g., skin peeling and face lift). The details of the database and performance evaluation of several well known face recognition algorithms is available in the paper mentioned below.

    The list of URLs is compiled in a text file along with a tool to download the images present at these URLs. The tool will download the images and store them at the specified location.
  • Text file containing the URLs
  • Tool to download the images
  • To obtain the password for the compressed file, email the duly filled license agreement to anushs@iiitd.ac.in with the subject line "License agreement for Plastic Surgery Face Database".
    NOTE: The license agreement has to be signed by faculty members or equivalent. It is not possible to accept license agreements signed by students and temporary researchers

    This database is available only for research and educational purpose and not for any commercial use. If you use the database in any publications or reports, you must refer to the following paper:
  • R. Singh, M. Vatsa, H.S. Bhatt, S. Bharadwaj, A. Noore and S.S. Nooreyezdan, Plastic Surgery: A New Dimension to Face Recognition, In IEEE Transaction on Information Forensics and Security, Vol. 5, No. 3, pp. 441-448, 2010.

    Disclaimer: The images in the plastic surgery database are downloaded from the internet and some of the subjects appear on different websites under different surgery labels. Therefore, this database may have some repetition of subjects across different types of surgeries. We have figured out multiple cases with such inconsistencies and provided an errata. If you come across some other cases as well, kindly report it to us.

    Please find the text file of errata. The images seperated by comma(,) represent the redundant entries in the database.