activity
20192025
most citedCineFilter: Unsupervised Filtering for Real Time Autonomous Camera Systems

1 citations · 1 across the 6 of their papers we have counts for

collaborators

7 papers

cs.IT2025

On the Service Rate Region of Reed-Muller Codes

Hoang Ly, Emina Soljanin, V. Lalitha

We study the Service Rate Region of Reed-Muller codes in the context of distributed storage systems. The service rate region is a convex polytope comprising all achievable data acc…

cs.CV2024

MetricGold: Leveraging Text-To-Image Latent Diffusion Models for Metric Depth Estimation

Ansh Shah, K Madhava Krishna

Recovering metric depth from a single image remains a fundamental challenge in computer vision, requiring both scene understanding and accurate scaling. While deep learning has adv…

cs.CL2024

Major Entity Identification: A Generalizable Alternative to Coreference Resolution

Kawshik Manikantan, Shubham Toshniwal, Makarand Tapaswi +1

The limited generalization of coreference resolution (CR) models has been a major bottleneck in the task's broad application. Prior work has identified annotation differences, espe…

q-bio.NC2024

Graph learning methods to extract empathy supporting regions in a naturalistic stimuli fMRI

Sasanka GRS, Ayushi Agrawal, Santosh Nannuru +1

Functional MRI (fMRI) research, employing naturalistic stimuli like movies, explores brain network interactions in complex cognitive processes such as empathy. The empathy network…

cs.CY2020

The State of AI Ethics Report (October 2020)

Abhishek Gupta, Alexandrine Royer, Victoria Heath +12

The 2nd edition of the Montreal AI Ethics Institute's The State of AI Ethics captures the most relevant developments in the field of AI Ethics since July 2020. This report aims to…

cs.CV2019★ 1 cited

CineFilter: Unsupervised Filtering for Real Time Autonomous Camera Systems

Sudheer Achary, K L Bhanu Moorthy, Syed Ashar Javed +3

Autonomous camera systems are often subjected to an optimization/filtering operation to smoothen and stabilize the rough trajectory estimates. Most common filtering techniques do r…

cs.CV2019

Low-Cost Transfer Learning of Face Tasks

Thrupthi Ann John, Isha Dua, Vineeth N Balasubramanian +1

Do we know what the different filters of a face network represent? Can we use this filter information to train other tasks without transfer learning? For instance, can age, head po…