Deep learning

Najmeddine Dhieb

Research Engineer, Electrical and Computer Engineering

artificial intelligence Deep learning Generative AI and LLMs

Aznaur Aliev

M.S. Student

AI Deep learning Computer Vision Reinforcement Learning

Indoor 3D Scene Understanding Using Depth Sensors

Jean Lahoud, Ph.D., Electrical and Computer Engineering

May 28, 16:00 - 18:00

KAUST

Computer Vision 3D object detection Deep learning

One of the main goals in computer vision is to achieve a human-like understanding of images. This understanding has been recently represented in various forms, including image classification, object detection, semantic segmentation, among many others. Nevertheless, image understanding has been mainly studied in the 2D image frame, so more information is needed to relate them to the 3D world. With the emergence of 3D sensors (e.g. the Microsoft Kinect), which provide depth along with color information, the task of propagating 2D knowledge into 3D becomes more attainable and enables interaction between a machine (e.g. robot) and its environment. This dissertation focuses on three aspects of indoor 3D scene understanding: (1) 2D-driven 3D object detection for single frame scenes with inherent 2D information, (2) 3D object instance segmentation for 3D reconstructed scenes, and (3) using room and floor orientation for automatic labeling of indoor scenes that could be used for self-supervised object segmentation. These methods allow capturing of physical extents of 3D objects, such as their sizes and actual locations within a scene.

Fabian and Victor participate in the annual MSR Summer School!

1 min read · Fri, Jul 8 2016

PhD Summer School 2016 Computer Vision Deep learning

Two IVUL Ph.D. students (Fabian Caba and Victor Escorcia) participate in the annual MSR Summer School.

Adel is invited to give a talk in EECVC on "Optimization meets Deep Learning"

1 min read · Tue, Jan 22 2019

Deep learning optimization EECVC

Adel is invited to give a talk in EECVC on "Optimization meets Deep Learning". It is a 45 minutes talk scheduled on the 6th of July 2019.

IVUL paper Wins Best Poster award at CVPR Workshop

1 min read · Mon, Jun 21 2021

Computer Vision Deep learning artificial intelligence

A paper by IVUL members won a Best Poster award at the LatinX in Computer Vision Workshop at CVPR 2021, the world-renowned venue for research in Computer Vision. The paper, "BAOD: Budget-Aware Object Detection", was written by four IVUL members, Alejandro Pardo, Mengmeng Frost Xu, Ali K. Thabet, and Bernard Ghanem, in collaboration with Professor Pablo Arbeláez, from Universidad de los Andes. The paper studies the efficiency with which object-detection systems learn when constrained by limited budgets. We congratulate the authors!

Silvio Giancola

Research Scientist, Image and Video Understanding Lab

Computer Vision artificial intelligence Technology Transfer Deep learning 3D understanding Sports start-up robotics

Silvio Giancola is a Research Scientist at King Abdullah University of Science and Technology (KAUST), under the supervision of Prof. Bernard Ghanem in the Image and Video Understanding Laboratory (IVUL), part of the Center of Excellence for Generative AI (GenAI).

Noor Bafageeh

M.S., Computer Science

Computer Vision Deep learning machine learning

Noor Bafageeh was a Master student in Computer Science Program under the supervision of Professor Bernard Ghanem at Visual Computing Center (VCC) at King Abdullah university of Science and Technology (KAUST). Education and Career Noor earned her bachelor degree in Computer Science from Effat University in Jeddah in 2016. She joined KAUST and received her master degree in Computer Science in 2018. Research Interest She is interested in computer vision, machine learning, Generative Adversarial Networks (GAN) and deep learning. Education Profile M.S., Computer Science, King Abdullah University of

Mengmeng Xu (Frost)

Ph.D. Student, Electrical and Computer Engineering

Computer Vision Deep learning Video Understanding

Mengmeng Xu (Frost) was an Electrical and Computer Engineering PhD Student in Image and Video Understanding Lab (IVUL) Group at King Abdullah University of Science and Technology (KAUST) under the supervision of Professor Bernard Ghanem. He is currently continuing his Ph.D. Education and Early Career Mengmeng obtained his bachelor's degree in Optics and Optical Sciences from Zhejiang University in China in 2017 and his Master's Degree from KAUST under the supervision of Professor Bernard Ghanem. Research Interests He is mainly focusing on problems that arise in computer vision, including

Matthias Mueller

Ph.D., Electrical and Computer Engineering

machine learning Deep learning Computer Vision robotics

Matthias Mueller was an Electrical and Computer Engineering Ph.D. candidate in Image and Video Understanding Lab (IVUL) Group at Visual Computing Center (VCC) under the supervision of Prof. Bernard Ghanem at King Abdullah University of Science and Technology (KAUST). Education and Early Career Matthias graduated with a B.Sc. in Electrical Engineering and Math Minor from Texas A&M University in 2011. After graduation, he joined P+Z Engineering in Munich, Germany as an Electrical Engineer and worked for 3 years on the development of mild-hybrid electric machines at BMW. In 2014, he started his M

Juan C. Pérez

Ph.D., Computer Science

Computer Vision Deep learning

Juan C. Pérez was a Ph.D. Candidate in the computer science program under Professor Bernard Ghanem's supervision at the Image and Video Understanding Lab at King Abdullah University of Science and Technology (KAUST). Before joining KAUST, Juan obtained a master's degree and a bachelor's degree ( cum laude) in biomedical engineering from Universidad de Los Andes, Colombia.

Jia-Hong Huang

M.S., Electrical and Computer Engineering

machine learning Computer Vision Deep learning

Jia-Hong Huang was a Master's student in the Electrical and Computer Engineering Program under the supervision of Professor Bernard Ghanem at Visual Computing Center (VCC) at King Abdullah University of Science and Technology (KAUST). Education and Career Jia-Hong earned a double major bachelor's degree in Statistics and Mathematical Science from National Chengchi University in Taiwan in 2014. He received his master's degree in Mechanical Engineering from National Taiwan University in 2016. After that, he joined KAUST and received his second master's degree in Electrical Engineering in 2018

Jean Lahoud

Ph.D., Electrical and Computer Engineering

Computer Vision 3D object detection Deep learning

Jean Lahoud was a Ph. D. student in Image and Video Understanding Lab (IVUL) Group under the supervision of Prof. Bernard Ghanem at KAUST. Education and Early Career Jean Lahoud received his Bachelor of Engineering in Mechanical Engineering from Notre Dame University in Lebanon in 2012. In 2014, he obtained his Master of Engineering degree in the same field from American University of Beirut in Lebanon. Before joining KAUST, Jean was a product manager at Murex systems in Lebanon. Research Interest Jean Lahoud is interested in 3D scene understanding using RGB-D sensors. Honors and Awards In

Jian Zhang

Postdoctoral Research Fellow, Image and Video Understanding Lab

Deep learning Compressive Sensing

Jian Zhang was a Postdoctoral Research Fellow at the Visual Computing Center (VCC) in King Abdullah University of Science and Technology (KAUST), working with Professor Bernard Ghanem in the Image and Video Understanding Laboratory (IVUL). Currently, he is an Assistant Professor at the School of Electronic and Computer Engineering, Peking University Shenzhen Graduate School, Shenzhen, China. Education and Early Career Jian Zhang joined Harbin Institute of Technology (HIT) in 2003 to start his academic life. In 2007, he received a bachelor degree in Applied Mathematics. After that in 2009, he

Jesus Zarzar

Ph.D., Electrical and Computer Engineering

Computer Vision Deep learning

Jesus Zarzar was an Electrical and Computer Engineering PhD student in Image and Video Understanding Lab (IVUL) Group at King Abdullah University of Science and Technology (KAUST) under the supervision of Professor Bernard Ghanem. Education and Early Career Jesus obtained his bachelor degree in Electrical and Computer Engineering from UT Austin, United States in 2017 before obtaining his Master's Degree from KAUST under the supervision of Professor Bernard Ghanem. Publications Education Profile B.S., Electrical and Computer Engineering, UT Austin, Austin, United States, 2017

Hasan Abed Al Kader Hammoud

Ph.D. Student, Electrical and Computer Engineering

Deep learning machine learning Computer Vision

Hasan is an Electrical and Computer Engineering MS/Ph.D. student in Image and Video Understanding Lab (IVUL) Group in Visual Computing Center (VCC) at King Abdullah University of Science and Technology (KAUST) under the supervision of Professor Bernard Ghanem. Education and Early Career Hasan obtained his bachelor's degree in Electrical and Computer Engineering from American University of Beirut in 2020. He joined KAUST in 2020 to pursue his MS and PhD degrees. Research Interest Deep Learning Machine Learning Computer Vision Publications Rapid Adaptation in Online Continual Learning: Are We

Guohao Li

Ph.D. Student, Computer Science

Computer Vision Deep learning

Guohao Li is a Ph. D. candidate in Image and Video Understanding Lab (IVUL) Group under the supervision of Prof. Bernard Ghanem at KAUST. Education and Early Career Guohao Li obtained a Bachelor’s Degree in Communication Engineering from Harbin Institute of Technology in China in 2015. In 2018, he received his Master Degree in Communication and Information System from Chinese Academy of Science in China. Research Interest His primary research interest is in Computer Vision and Deep Learning. Publications Education Profile M.Sc. in Communication and Information System, Chinese Academy of

Chen Zhao

Research Scientist, Electrical and Computer Engineering

Deep learning Computer Vision Compressive Sensing image and video processing Video Understanding Reversible networks

Chen Zhao is a Research Scientist at KAUST, and Lead of the Video Understanding Theme in the Image and Video Understanding Lab. She received her Ph.D. degree from Peking University, China in 2016. She studied in University of Washington, US from 2012 to 2013, and at the National Institute of Informatics, Japan in 2016. She has published 40+ papers on representative journals and conferences such as TPAMI, CVPR, ICCV, ECCV, and has received over 3000 citations according to Google Scholar.

Cheng Zheng

Software Engineer, Image and Video Understanding Lab

Computer Vision Deep learning generative adversarial network

Cheng Zheng is a Software Engineer Consultant working with Professor Bernard Ghanem in the Image and Video Understanding Lab (IVUL) in the Visual Computing Center at King Abdullah University of Science and Technology (KAUST). Education and Early Career Cheng Zheng received his Bachelor's degree in Computer Science from Beijing University of Posts and Telecommunications (BUPT), China, in 2009. He received his Master's degree from the University of Chinese Academy of Sciences (UCAS), China, In 2012. Before joining KAUST, in 2012, he worked as a software engineer at NetEase Games in China. In

Ali Thabet

Research Scientist, Image and Video Understanding Lab

Computer Vision Deep learning point cloud

Ali Thabet is a Research Scientist at the Visual Computing Center (VCC) in King Abdullah University of Science and Technology (KAUST), working with Professor Bernard Ghanem in the Image and Video Understanding Laboratory (IVUL). Education and Early Career Ali obtained a bachelor of engineering degree in Electrical Engineering, from the American University of Beirut in Beirut, Lebanon in 2006. He holds a Ph.D. in Computer Science from the University of Dundee in Dundee, UK. He joined KAUST as a Postdoctoral Fellow in the Visual Computing Center (VCC) from 2012 to 2014. After that, he worked as

Abdulellah Abualshour

M.S., Computer Science

machine learning Deep learning data science

Abdulellah Abualshour is a Ph.D. student under the supervision of Prof. Bernard Ghanem at the Visual Computing Center (VCC) in King Abdullah University of Science and Technology (KAUST). Education and Early Career Abdulellah was chosen to join the KAUST Gifted Student Program (KGSP). He is a graduate of Rutgers University where he received a B.S. degree in Computer Science, with a focus on data science and artificial intelligence. Regarding his early career, Abdulellah did many internships during his studies. In 2015, he worked for 1 year as a Public Relations Officer at Rutgers U niversity in

Abdullah Hamdi

Ph.D. Student, Electrical and Computer Engineering

Deep learning machine learning Computer Vision

Abdullah Hamdi is a Ph.D. candidate in Image and Video Understanding Lab (IVUL) Group at King Abdullah University of Science and Technology (KAUST) under the supervision of Professor Bernard Ghanem. Education and Early Career In 2016, Abdullah Hamdi obtained his bachelor degree in Electrical Engineering from King Fahd University of Petroleum and Minerals (KFUPM) in Dhahran, Saudi Arabia. After that, he joined KAUST to proceed in the same field of study and received his master degree in 2017 in Computer Vision track. Research Interest Machine Learning Robustness of Deep Learning Computer Vision