most citedGraph CNN for Moving Object Detection in Complex Environments from Unseen Videos

30 citations · 31 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2023

Unsupervised Mutual Transformer Learning for Multi-Gigapixel Whole Slide Image Classification

Sajid Javed, Arif Mahmood, Talha Qaiser +2

Classification of gigapixel Whole Slide Images (WSIs) is an important prediction task in the emerging area of computational pathology. There has been a surge of research in deep le…

cs.CV2023

DFR-FastMOT: Detection Failure Resistant Tracker for Fast Multi-Object Tracking Based on Sensor Fusion

Mohamed Nagy, Majid Khonji, Jorge Dias +1

Persistent multi-object tracking (MOT) allows autonomous vehicles to navigate safely in highly dynamic environments. One of the well-known challenges in MOT is object occlusion whe…

cs.LG2023

Higher-order Sparse Convolutions in Graph Neural Networks

Jhony H. Giraldo, Sajid Javed, Arif Mahmood +2

Graph Neural Networks (GNNs) have been applied to many problems in computer sciences. Capturing higher-order relationships between nodes is crucial to increase the expressive power…

cs.CV2022

Person Monitoring by Full Body Tracking in Uniform Crowd Environment

Zhibo Zhang, Omar Alremeithi, Maryam Almheiri +4

Full body trackers are utilized for surveillance and security purposes, such as person-tracking robots. In the Middle East, uniform crowd environments are the norm which challenges…

cs.CV20221 cited

Learning Branched Fusion and Orthogonal Projection for Face-Voice Association

Muhammad Saad Saeed, Shah Nawaz, Muhammad Haris Khan +3

Recent years have seen an increased interest in establishing association between faces and voices of celebrities leveraging audio-visual information from YouTube. Prior works adopt…

cs.CV202230 cited

Graph CNN for Moving Object Detection in Complex Environments from Unseen Videos

Jhony H. Giraldo, Sajid Javed, Naoufel Werghi +1

Moving Object Detection (MOD) is a fundamental step for many computer vision applications. MOD becomes very challenging when a video sequence captured from a static or moving camer…