176 citations · 457 across the 18 of their papers we have counts for
19 papers
OrgAccess: A Benchmark for Role Based Access Control in Organization Scale LLMs
Debdeep Sanyal, Umakanta Maharana, Yash Sinha +4
Role-based access control (RBAC) and hierarchical structures are foundational to how information flows and decisions are made within virtually all organizations. As the potential o…
UnStar: Unlearning with Self-Taught Anti-Sample Reasoning for LLMs
Yash Sinha, Murari Mandal, Mohan Kankanhalli
The key components of machine learning are data samples for training, model for learning patterns, and loss function for optimizing accuracy. Analogously, unlearning can potentiall…
Multi-Modal Recommendation Unlearning for Legal, Licensing, and Modality Constraints
Yash Sinha, Murari Mandal, Mohan Kankanhalli
User data spread across multiple modalities has popularized multi-modal recommender systems (MMRS). They recommend diverse content such as products, social media posts, TikTok reel…
Distill to Delete: Unlearning in Graph Networks with Knowledge Distillation
Yash Sinha, Murari Mandal, Mohan Kankanhalli
Graph unlearning has emerged as a pivotal method to delete information from a pre-trained graph neural network (GNN). One may delete nodes, a class of nodes, edges, or a class of e…
Efficient Neural Architecture Search for Emotion Recognition
Monu Verma, Murari Mandal, Satish Kumar Reddy +2
Automated human emotion recognition from facial expressions is a well-studied problem and still remains a very challenging task. Some efficient or accurate deep learning models hav…
Can Bad Teaching Induce Forgetting? Unlearning in Deep Networks using an Incompetent Teacher
Vikram S Chundawat, Ayush K Tarun, Murari Mandal +1
Machine unlearning has become an important area of research due to an increasing need for machine learning (ML) applications to comply with the emerging data privacy regulations. I…
Zero-Shot Machine Unlearning
Vikram S Chundawat, Ayush K Tarun, Murari Mandal +1
Modern privacy regulations grant citizens the right to be forgotten by products, services and companies. In case of machine learning (ML) applications, this necessitates deletion o…
Fast Yet Effective Machine Unlearning
Ayush K Tarun, Vikram S Chundawat, Murari Mandal +1
Unlearning the data observed during the training of a machine learning (ML) model is an important task that can play a pivotal role in fortifying the privacy and security of ML-bas…
Learning to Enhance Visual Quality via Hyperspectral Domain Mapping
Harsh Sinha, Aditya Mehta, Murari Mandal +1
Deep learning based methods have achieved remarkable success in image restoration and enhancement, but most such methods rely on RGB input images. These methods fail to take into a…
Improving Aerial Instance Segmentation in the Dark with Self-Supervised Low Light Enhancement
Prateek Garg, Murari Mandal, Pratik Narang
Low light conditions in aerial images adversely affect the performance of several vision based applications. There is a need for methods that can efficiently remove the low light a…
Domain-Aware Unsupervised Hyperspectral Reconstruction for Aerial Image Dehazing
Aditya Mehta, Harsh Sinha, Murari Mandal +1
Haze removal in aerial images is a challenging problem due to considerable variation in spatial details and varying contrast. Changes in particulate matter density often lead to de…
MOR-UAV: A Benchmark Dataset and Baselines for Moving Object Recognition in UAV Videos
Murari Mandal, Lav Kush Kumar, Santosh Kumar Vipparthi
Visual data collected from Unmanned Aerial Vehicles (UAVs) has opened a new frontier of computer vision that requires automated analysis of aerial images/videos. However, the exist…
NTIRE 2020 Challenge on NonHomogeneous Dehazing
Codruta O. Ancuti, Cosmin Ancuti, Florin-Alexandru Vasluianu +49
This paper reviews the NTIRE 2020 Challenge on NonHomogeneous Dehazing of images (restoration of rich details in hazy image). We focus on the proposed solutions and their results e…
3D CNN with Localized Residual Connections for Hyperspectral Image Classification
Shivangi Dwivedi, Murari Mandal, Shekhar Yadav +1
In this paper we propose a novel 3D CNN network with localized residual connections for hyperspectral image classification. Our work chalks a comparative study with the existing me…
SSSDET: Simple Short and Shallow Network for Resource Efficient Vehicle Detection in Aerial Scenes
Murari Mandal, Manal Shah, Prashant Meena +1
Detection of small-sized targets is of paramount importance in many aerial vision-based applications. The commonly deployed low cost unmanned aerial vehicles (UAVs) for aerial scen…
AVDNet: A Small-Sized Vehicle Detection Network for Aerial Visual Data
Murari Mandal, Manal Shah, Prashant Meena +2
Detection of small-sized targets in aerial views is a challenging task due to the smallness of vehicle size, complex background, and monotonic object appearances. In this letter, w…
Challenges in Time-Stamp Aware Anomaly Detection in Traffic Videos
Kuldeep Marotirao Biradar, Ayushi Gupta, Murari Mandal +1
Time-stamp aware anomaly detection in traffic videos is an essential task for the advancement of the intelligent transportation system. Anomaly detection in videos is a challenging…
Multichannel Distributed Local Pattern for Content Based Indexing and Retrieval
Sonakshi Mathur, Mallika Chaudhary, Hemant Verma +3
A novel color feature descriptor, Multichannel Distributed Local Pattern (MDLP) is proposed in this manuscript. The MDLP combines the salient features of both local binary and loca…
CANDID: Robust Change Dynamics and Deterministic Update Policy for Dynamic Background Subtraction
Murari Mandal, Prafulla Saxena, Santosh Kumar Vipparthi +1
Background subtraction in video provides the preliminary information which is essential for many computer vision applications. In this paper, we propose a sequence of approaches na…