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20172021
most citedDeep Learning for Face Recognition: Pride or Prejudiced?

40 citations · 50 across the 6 of their papers we have counts for

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15 papers · 1 filter

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.CV20201 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…

cs.CV201940 cited

Deep Learning for Face Recognition: Pride or Prejudiced?

Shruti Nagpal, Maneet Singh, Richa Singh +1

Do very high accuracies of deep networks suggest pride of effective AI or are deep networks prejudiced? Do they suffer from in-group biases (own-race-bias and own-age-bias), and mi…

cs.CV20195 cited

A Comprehensive Overview of Biometric Fusion

Maneet Singh, Richa Singh, Arun Ross

The performance of a biometric system that relies on a single biometric modality (e.g., fingerprints only) is often stymied by various factors such as poor data quality or limited…

cs.CV2018

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…