activity
20172022
most citedCNN-Based Prediction of Frame-Level Shot Importance for Video Summarization

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

collaborators

5 papers

cs.CV20221 cited

LOCL: Learning Object-Attribute Composition using Localization

Satish Kumar, ASM Iftekhar, Ekta Prashnani +1

This paper describes LOCL (Learning Object Attribute Composition using Localization) that generalizes composition zero shot learning to objects in cluttered and more realistic sett…

cs.CV20221 cited

What to look at and where: Semantic and Spatial Refined Transformer for detecting human-object interactions

A S M Iftekhar, Hao Chen, Kaustav Kundu +3

We propose a novel one-stage Transformer-based semantic and spatial refined transformer (SSRT) to solve the Human-Object Interaction detection task, which requires to localize huma…

cs.CV20201 cited

StressNet: Detecting Stress in Thermal Videos

Satish Kumar, A S M Iftekhar, Michael Goebel +7

Precise measurement of physiological signals is critical for the effective monitoring of human vital signs. Recent developments in computer vision have demonstrated that signals su…

cs.CV2020

VSGNet: Spatial Attention Network for Detecting Human Object Interactions Using Graph Convolutions

Oytun Ulutan, A S M Iftekhar, B. S. Manjunath

Comprehensive visual understanding requires detection frameworks that can effectively learn and utilize object interactions while analyzing objects individually. This is the main o…

cs.CV20171 cited

CNN-Based Prediction of Frame-Level Shot Importance for Video Summarization

Mohaiminul Al Nahian, A. S. M. Iftekhar, Mohammad Tariqul Islam +2

In the Internet, ubiquitous presence of redundant, unedited, raw videos has made video summarization an important problem. Traditional methods of video summarization employ a heuri…