most citedDemography-based Facial Retouching Detection using Subclass Supervised Sparse Autoencoder

3 citations · 3 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV2017

Synthetic Iris Presentation Attack using iDCGAN

Naman Kohli, Daksha Yadav, Mayank Vatsa +2

Reliability and accuracy of iris biometric modality has prompted its large-scale deployment for critical applications such as border control and national ID projects. The extensive…

cs.CV2017

Face Sketch Matching via Coupled Deep Transform Learning

Shruti Nagpal, Maneet Singh, Richa Singh +3

Face sketch to digital image matching is an important challenge of face recognition that involves matching across different domains. Current research efforts have primarily focused…

cs.CV2017

On Matching Skulls to Digital Face Images: A Preliminary Approach

Shruti Nagpal, Maneet Singh, Arushi Jain +3

Forensic application of automatically matching skull with face images is an important research area linking biometrics with practical applications in forensics. It is an opportunit…

cs.CV2017

Gender and Ethnicity Classification of Iris Images using Deep Class-Encoder

Maneet Singh, Shruti Nagpal, Mayank Vatsa +3

Soft biometric modalities have shown their utility in different applications including reducing the search space significantly. This leads to improved recognition performance, redu…

cs.CV20173 cited

Demography-based Facial Retouching Detection using Subclass Supervised Sparse Autoencoder

Aparna Bharati, Mayank Vatsa, Richa Singh +2

Digital retouching of face images is becoming more widespread due to the introduction of software packages that automate the task. Several researchers have introduced algorithms to…