activity
20172023
most citedDeep Learning for Face Recognition: Pride or Prejudiced?

40 citations · 59 across the 12 of their papers we have counts for

collaborators

18 papers

cs.LG2023★ 1 cited

GroupMixNorm Layer for Learning Fair Models

Anubha Pandey, Aditi Rai, Maneet Singh +2

Recent research has identified discriminatory behavior of automated prediction algorithms towards groups identified on specific protected attributes (e.g., gender, ethnicity, age g…

cs.CL2021★ 3 cited

Morality-based Assertion and Homophily on Social Media: A Cultural Comparison between English and Japanese Languages

Maneet Singh, Rishemjit Kaur, Akiko Matsuo +2

Moral psychology is a domain that deals with moral identity, appraisals and emotions. Previous work has primarily focused on moral development and the associated role of culture. K…

cs.LG2021★ 1 cited

Semi-supervised Learning for Marked Temporal Point Processes

Shivshankar Reddy, Anand Vir Singh Chauhan, Maneet Singh +1

Temporal Point Processes (TPPs) are often used to represent the sequence of events ordered as per the time of occurrence. Owing to their flexible nature, TPPs have been used to mod…

cs.CV2021

Enhancing Fine-Grained Classification for Low Resolution Images

Maneet Singh, Shruti Nagpal, Mayank Vatsa +1

Low resolution fine-grained classification has widespread applicability for applications where data is captured at a distance such as surveillance and mobile photography. While fin…

cs.CV2020★ 1 cited

On the Robustness of Face Recognition Algorithms Against Attacks and Bias

Richa Singh, Akshay Agarwal, Maneet Singh +2

Face recognition algorithms have demonstrated very high recognition performance, suggesting suitability for real world applications. Despite the enhanced accuracies, robustness of…

cs.CV2019

Dual Directed Capsule Network for Very Low Resolution Image Recognition

Maneet Singh, Shruti Nagpal, Richa Singh +1

Very low resolution (VLR) image recognition corresponds to classifying images with resolution 16x16 or less. Though it has widespread applicability when objects are captured at a v…