activity
20182022
most citedSubmodlib: A Submodular Optimization Library

6 citations · 11 across the 4 of their papers we have counts for

collaborators

10 papers

cs.LG20226 cited

Submodlib: A Submodular Optimization Library

Vishal Kaushal, Ganesh Ramakrishnan, Rishabh Iyer

Submodular functions are a special class of set functions which naturally model the notion of representativeness, diversity, coverage etc. and have been shown to be computationally…

cs.LG2021

Submodular Mutual Information for Targeted Data Subset Selection

Suraj Kothawade, Vishal Kaushal, Ganesh Ramakrishnan +2

With the rapid growth of data, it is becoming increasingly difficult to train or improve deep learning models with the right subset of data. We show that this problem can be effect…

cs.CV20215 cited

How Good is a Video Summary? A New Benchmarking Dataset and Evaluation Framework Towards Realistic Video Summarization

Vishal Kaushal, Suraj Kothawade, Anshul Tomar +2

Automatic video summarization is still an unsolved problem due to several challenges. The currently available datasets either have very short videos or have few long videos of only…

cs.LG2020

A Unified Framework for Generic, Query-Focused, Privacy Preserving and Update Summarization using Submodular Information Measures

Vishal Kaushal, Suraj Kothawade, Ganesh Ramakrishnan +3

We study submodular information measures as a rich framework for generic, query-focused, privacy sensitive, and update summarization tasks. While past work generally treats these p…

cs.CV2020

Realistic Video Summarization through VISIOCITY: A New Benchmark and Evaluation Framework

Vishal Kaushal, Suraj Kothawade, Rishabh Iyer +1

Automatic video summarization is still an unsolved problem due to several challenges. We take steps towards making automatic video summarization more realistic by addressing them.…

cs.CV2019

Demystifying Multi-Faceted Video Summarization: Tradeoff Between Diversity,Representation, Coverage and Importance

Vishal Kaushal, Rishabh Iyer, Khoshrav Doctor +6

This paper addresses automatic summarization of videos in a unified manner. In particular, we propose a framework for multi-faceted summarization for extractive, query base and ent…