22 citations · 45 across the 12 of their papers we have counts for
12 papers
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos
Zijia Lu, A S M Iftekhar, Gaurav Mittal +6
Long Video Temporal Grounding (LVTG) aims at identifying specific moments within lengthy videos based on user-provided text queries for effective content retrieval. The approach ta…
Hummingbird: High Fidelity Image Generation via Multimodal Context Alignment
Minh-Quan Le, Gaurav Mittal, Tianjian Meng +5
While diffusion models are powerful in generating high-quality, diverse synthetic data for object-centric tasks, existing methods struggle with scene-aware tasks such as Visual Que…
BLoad: Enhancing Neural Network Training with Efficient Sequential Data Handling
Raphael Ruschel, A. S. M. Iftekhar, B. S. Manjunath +1
The increasing complexity of modern deep neural network models and the expanding sizes of datasets necessitate the development of optimized and scalable training methods. In this w…
MethaneMapper: Spectral Absorption aware Hyperspectral Transformer for Methane Detection
Satish Kumar, Ivan Arevalo, ASM Iftekhar +1
Methane (CH) is the chief contributor to global climate change. Recent Airborne Visible-Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) has been very useful in quanti…
DDS: Decoupled Dynamic Scene-Graph Generation Network
A S M Iftekhar, Raphael Ruschel, Satish Kumar +2
Scene-graph generation involves creating a structural representation of the relationships between objects in a scene by predicting subject-object-relation triplets from input data.…
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…
Context-Driven Detection of Invertebrate Species in Deep-Sea Video
R. Austin McEver, Bowen Zhang, Connor Levenson +2
Each year, underwater remotely operated vehicles (ROVs) collect thousands of hours of video of unexplored ocean habitats revealing a plethora of information regarding biodiversity…
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…
GTNet:Guided Transformer Network for Detecting Human-Object Interactions
A S M Iftekhar, Satish Kumar, R. Austin McEver +2
The human-object interaction (HOI) detection task refers to localizing humans, localizing objects, and predicting the interactions between each human-object pair. HOI is considered…
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…
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…
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…