81 citations · 124 across the 8 of their papers we have counts for
5 papers · 1 filter
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…
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…