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20182021
most citedEvaluating Empathetic Chatbots in Customer Service Settings

8 citations · 9 across the 3 of their papers we have counts for

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7 papers · 1 filter

cs.CV2021

MD-CSDNetwork: Multi-Domain Cross Stitched Network for Deepfake Detection

Aayushi Agarwal, Akshay Agarwal, Sayan Sinha +2

The rapid progress in the ease of creating and spreading ultra-realistic media over social platforms calls for an urgent need to develop a generalizable deepfake detection techniqu…

cs.CV2020

WaveTransform: Crafting Adversarial Examples via Input Decomposition

Divyam Anshumaan, Akshay Agarwal, Mayank Vatsa +1

Frequency spectrum has played a significant role in learning unique and discriminating features for object recognition. Both low and high frequency information present in images ha…

cs.CV2020

Attack Agnostic Adversarial Defense via Visual Imperceptible Bound

Saheb Chhabra, Akshay Agarwal, Richa Singh +1

The high susceptibility of deep learning algorithms against structured and unstructured perturbations has motivated the development of efficient adversarial defense algorithms. How…

cs.CV2020

MixNet for Generalized Face Presentation Attack Detection

Nilay Sanghvi, Sushant Kumar Singh, Akshay Agarwal +2

The non-intrusive nature and high accuracy of face recognition algorithms have led to their successful deployment across multiple applications ranging from border access to mobile…

cs.CV2020

Generalized Iris Presentation Attack Detection Algorithm under Cross-Database Settings

Mehak Gupta, Vishal Singh, Akshay Agarwal +2

Presentation attacks are posing major challenges to most of the biometric modalities. Iris recognition, which is considered as one of the most accurate biometric modality for perso…

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…