85 citations · 214 across the 16 of their papers we have counts for
16 papers
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…
Hear The Flow: Optical Flow-Based Self-Supervised Visual Sound Source Localization
Dennis Fedorishin, Deen Dayal Mohan, Bhavin Jawade +2
Learning to localize the sound source in videos without explicit annotations is a novel area of audio-visual research. Existing work in this area focuses on creating attention maps…
Active Face Frontalization using Commodity Unmanned Aerial Vehicles
Nagashri Lakshminarayana, Yifang Liu, Karthik Dantu +2
This paper describes a system by which Unmanned Aerial Vehicles (UAVs) can gather high-quality face images that can be used in biometric identification tasks. Success in face-based…
Article citation study: Context enhanced citation sentiment detection
Vishal Vyas, Kumar Ravi, Vadlamani Ravi +3
Citation sentimet analysis is one of the little studied tasks for scientometric analysis. For citation analysis, we developed eight datasets comprising citation sentences, which ar…
CAN: Composite Appearance Network for Person Tracking and How to Model Errors in a Tracking System
Neeti Narayan, Nishant Sankaran, Srirangaraj Setlur +1
Tracking multiple people across multiple cameras is an open problem. It is typically divided into two tasks: (i) single-camera tracking (SCT) - identify trajectories in the same sc…
On Optimality Conditions for Auto-Encoder Signal Recovery
Devansh Arpit, Yingbo Zhou, Hung Q. Ngo +2
Auto-Encoders are unsupervised models that aim to learn patterns from observed data by minimizing a reconstruction cost. The useful representations learned are often found to be sp…
Normalization Propagation: A Parametric Technique for Removing Internal Covariate Shift in Deep Networks
Devansh Arpit, Yingbo Zhou, Bhargava U. Kota +1
While the authors of Batch Normalization (BN) identify and address an important problem involved in training deep networks-- Internal Covariate Shift-- the current solution has cer…
Maximum Entropy Binary Encoding for Face Template Protection
Rohit Kumar Pandey, Yingbo Zhou, Bhargava Urala Kota +1
In this paper we present a framework for secure identification using deep neural networks, and apply it to the task of template protection for face authentication. We use deep conv…
Deep Secure Encoding: An Application to Face Recognition
Rohit Pandey, Yingbo Zhou, Venu Govindaraju
In this paper we present Deep Secure Encoding: a framework for secure classification using deep neural networks, and apply it to the task of biometric template protection for faces…
Virtual Networks and Poverty Analysis in Senegal
Neeti Pokhriyal, Wen Dong, Venu Govindaraju
Do today's communication technologies hold potential to alleviate poverty? The mobile phone's accessibility and use allows us with an unprecedented volume of data on social interac…
Why Regularized Auto-Encoders learn Sparse Representation?
Devansh Arpit, Yingbo Zhou, Hung Ngo +1
While the authors of Batch Normalization (BN) identify and address an important problem involved in training deep networks-- \textit{Internal Covariate Shift}-- the current solutio…
Dimensionality Reduction with Subspace Structure Preservation
Devansh Arpit, Ifeoma Nwogu, Venu Govindaraju
Modeling data as being sampled from a union of independent subspaces has been widely applied to a number of real world applications. However, dimensionality reduction approaches th…
Is Joint Training Better for Deep Auto-Encoders?
Yingbo Zhou, Devansh Arpit, Ifeoma Nwogu +1
Traditionally, when generative models of data are developed via deep architectures, greedy layer-wise pre-training is employed. In a well-trained model, the lower layer of the arch…
An Analysis of Random Projections in Cancelable Biometrics
Devansh Arpit, Ifeoma Nwogu, Gaurav Srivastava +1
With increasing concerns about security, the need for highly secure physical biometrics-based authentication systems utilizing \emph{cancelable biometric} technologies is on the ri…