65 citations · 207 across the 20 of their papers we have counts for
23 papers
Dynamics Aware Quadrupedal Locomotion via Intrinsic Dynamics Head
Aman Arora, Nalini Ratha
Quadrupedal locomotion plays a critical role in enabling agile, versatile movement across complex terrains. Understanding and estimating the underlying physical dynamics are essent…
Multimodal Privacy-Preserving Entity Resolution with Fully Homomorphic Encryption
Susim Roy, Nalini Ratha
The canonical challenge of entity resolution within high-compliance sectors, where secure identity reconciliation is frequently confounded by significant data heterogeneity, includ…
Forget Less by Learning Together through Concept Consolidation
Arjun Ramesh Kaushik, Naresh Kumar Devulapally, Vishnu Suresh Lokhande +2
Custom Diffusion Models (CDMs) have gained significant attention due to their remarkable ability to personalize generative processes. However, existing CDMs suffer from catastrophi…
Learning Action Hierarchies via Hybrid Geometric Diffusion
Arjun Ramesh Kaushik, Nalini K. Ratha, Venu Govindaraju
Temporal action segmentation is a critical task in video understanding, where the goal is to assign action labels to each frame in a video. While recent advances leverage iterative…
Forget Less by Learning from Parents Through Hierarchical Relationships
Arjun Ramesh Kaushik, Naresh Kumar Devulapally, Vishnu Suresh Lokhande +2
Custom Diffusion Models (CDMs) offer impressive capabilities for personalization in generative modeling, yet they remain vulnerable to catastrophic forgetting when learning new con…
Shielding Latent Face Representations From Privacy Attacks
Arjun Ramesh Kaushik, Bharat Chandra Yalavarthi, Arun Ross +2
In today's data-driven analytics landscape, deep learning has become a powerful tool, with latent representations, known as embeddings, playing a central role in several applicatio…
Aligning Characteristic Descriptors with Images for Human-Expert-like Explainability
Bharat Chandra Yalavarthi, Nalini Ratha
In mission-critical domains such as law enforcement and medical diagnosis, the ability to explain and interpret the outputs of deep learning models is crucial for ensuring user tru…
Enhancing Authorship Attribution through Embedding Fusion: A Novel Approach with Masked and Encoder-Decoder Language Models
Arjun Ramesh Kaushik, Sunil Rufus R P, Nalini Ratha
The increasing prevalence of AI-generated content alongside human-written text underscores the need for reliable discrimination methods. To address this challenge, we propose a nov…
Towards Building Secure UAV Navigation with FHE-aware Knowledge Distillation
Arjun Ramesh Kaushik, Charanjit Jutla, Nalini Ratha
In safeguarding mission-critical systems, such as Unmanned Aerial Vehicles (UAVs), preserving the privacy of path trajectories during navigation is paramount. While the combination…
Confidential and Protected Disease Classifier using Fully Homomorphic Encryption
Aditya Malik, Nalini Ratha, Bharat Yalavarthi +3
With the rapid surge in the prevalence of Large Language Models (LLMs), individuals are increasingly turning to conversational AI for initial insights across various domains, inclu…
Enhancing Privacy and Security of Autonomous UAV Navigation
Vatsal Aggarwal, Arjun Ramesh Kaushik, Charanjit Jutla +1
Autonomous Unmanned Aerial Vehicles (UAVs) have become essential tools in defense, law enforcement, disaster response, and product delivery. These autonomous navigation systems req…
Enhancing Privacy in Face Analytics Using Fully Homomorphic Encryption
Bharat Yalavarthi, Arjun Ramesh Kaushik, Arun Ross +2
Modern face recognition systems utilize deep neural networks to extract salient features from a face. These features denote embeddings in latent space and are often stored as templ…
RidgeBase: A Cross-Sensor Multi-Finger Contactless Fingerprint Dataset
Bhavin Jawade, Deen Dayal Mohan, Srirangaraj Setlur +2
Contactless fingerprint matching using smartphone cameras can alleviate major challenges of traditional fingerprint systems including hygienic acquisition, portability and presenta…
HEFT: Homomorphically Encrypted Fusion of Biometric Templates
Luke Sperling, Nalini Ratha, Arun Ross +1
This paper proposes a non-interactive end-to-end solution for secure fusion and matching of biometric templates using fully homomorphic encryption (FHE). Given a pair of encrypted…
Efficient Encrypted Inference on Ensembles of Decision Trees
Kanthi Sarpatwar, Karthik Nandakumar, Nalini Ratha +4
Data privacy concerns often prevent the use of cloud-based machine learning services for sensitive personal data. While homomorphic encryption (HE) offers a potential solution by e…
Efficient CNN Building Blocks for Encrypted Data
Nayna Jain, Karthik Nandakumar, Nalini Ratha +2
Machine learning on encrypted data can address the concerns related to privacy and legality of sharing sensitive data with untrustworthy service providers. Fully Homomorphic Encryp…
Securing CNN Model and Biometric Template using Blockchain
Akhil Goel, Akshay Agarwal, Mayank Vatsa +2
Blockchain has emerged as a leading technology that ensures security in a distributed framework. Recently, it has been shown that blockchain can be used to convert traditional bloc…
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…
Diversity in Faces
Michele Merler, Nalini Ratha, Rogerio S. Feris +1
Face recognition is a long standing challenge in the field of Artificial Intelligence (AI). The goal is to create systems that accurately detect, recognize, verify, and understand…
Understanding Unequal Gender Classification Accuracy from Face Images
Vidya Muthukumar, Tejaswini Pedapati, Nalini Ratha +7
Recent work shows unequal performance of commercial face classification services in the gender classification task across intersectional groups defined by skin type and gender. Acc…
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…
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…
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…