81 citations · 275 across the 51 of their papers we have counts for
16 papers · 2 filters
Data Fine-tuning
Saheb Chhabra, Puspita Majumdar, Mayank Vatsa +1
In real-world applications, commercial off-the-shelf systems are utilized for performing automated facial analysis including face recognition, emotion recognition, and attribute pr…
Recognizing Disguised Faces in the Wild
Maneet Singh, Richa Singh, Mayank Vatsa +2
Research in face recognition has seen tremendous growth over the past couple of decades. Beginning from algorithms capable of performing recognition in constrained environments, th…
On Matching Faces with Alterations due to Plastic Surgery and Disguise
Saksham Suri, Anush Sankaran, Mayank Vatsa +1
Plastic surgery and disguise variations are two of the most challenging co-variates of face recognition. The state-of-art deep learning models are not sufficiently successful due t…
Heterogeneity Aware Deep Embedding for Mobile Periocular Recognition
Rishabh Garg, Yashasvi Baweja, Soumyadeep Ghosh +3
Mobile biometric approaches provide the convenience of secure authentication with an omnipresent technology. However, this brings an additional challenge of recognizing biometric p…
Supervised COSMOS Autoencoder: Learning Beyond the Euclidean Loss!
Maneet Singh, Shruti Nagpal, Mayank Vatsa +2
Autoencoders are unsupervised deep learning models used for learning representations. In literature, autoencoders have shown to perform well on a variety of tasks spread across mul…
Learning A Shared Transform Model for Skull to Digital Face Image Matching
Maneet Singh, Shruti Nagpal, Richa Singh +2
Human skull identification is an arduous task, traditionally requiring the expertise of forensic artists and anthropologists. This paper is an effort to automate the process of mat…
Supervised Mixed Norm Autoencoder for Kinship Verification in Unconstrained Videos
Naman Kohli, Daksha Yadav, Mayank Vatsa +2
Identifying kinship relations has garnered interest due to several applications such as organizing and tagging the enormous amount of videos being uploaded on the Internet. Existin…
Hierarchical Representation Learning for Kinship Verification
Naman Kohli, Mayank Vatsa, Richa Singh +2
Kinship verification has a number of applications such as organizing large collections of images and recognizing resemblances among humans. In this research, first, a human study i…
Class Representative Autoencoder for Low Resolution Multi-Spectral Gender Classification
Maneet Singh, Shruti Nagpal, Richa Singh +1
Gender is one of the most common attributes used to describe an individual. It is used in multiple domains such as human computer interaction, marketing, security, and demographic…
Anonymizing k-Facial Attributes via Adversarial Perturbations
Saheb Chhabra, Richa Singh, Mayank Vatsa +1
A face image not only provides details about the identity of a subject but also reveals several attributes such as gender, race, sexual orientation, and age. Advancements in machin…
Learning Structure and Strength of CNN Filters for Small Sample Size Training
Rohit Keshari, Mayank Vatsa, Richa Singh +1
Convolutional Neural Networks have provided state-of-the-art results in several computer vision problems. However, due to a large number of parameters in CNNs, they require a large…
Residual Codean Autoencoder for Facial Attribute Analysis
Akshay Sethi, Maneet Singh, Richa Singh +1
Facial attributes can provide rich ancillary information which can be utilized for different applications such as targeted marketing, human computer interaction, and law enforcemen…
Are you eligible? Predicting adulthood from face images via class specific mean autoencoder
Maneet Singh, Shruti Nagpal, Mayank Vatsa +1
Predicting if a person is an adult or a minor has several applications such as inspecting underage driving, preventing purchase of alcohol and tobacco by minors, and granting restr…
Unravelling Robustness of Deep Learning based Face Recognition Against Adversarial Attacks
Gaurav Goswami, Nalini Ratha, Akshay Agarwal +2
Deep neural network (DNN) architecture based models have high expressive power and learning capacity. However, they are essentially a black box method since it is not easy to mathe…
MagnifyMe: Aiding Cross Resolution Face Recognition via Identity Aware Synthesis
Maneet Singh, Shruti Nagpal, Richa Singh +2
Enhancing low resolution images via super-resolution or image synthesis for cross-resolution face recognition has been well studied. Several image processing and machine learning p…
SegDenseNet: Iris Segmentation for Pre and Post Cataract Surgery
Aditya Lakra, Pavani Tripathi, Rohit Keshari +2
Cataract is caused due to various factors such as age, trauma, genetics, smoking and substance consumption, and radiation. It is one of the major common ophthalmic diseases worldwi…