Walid Bousselham

I'm a PhD student at Bonn University, advised by Prof. Hilde Kuehne. I'm also participating in MIT-IBM Watson Sight and Sound Project.

My primary research area is deep learning for multimodal models. Particularly, I am interested in zero-shot adaptation of pretrained models for emerging behavior.

Prior to this, I finished my Master of Engineering in Applied Mathematics at ENSTA Paris in France and my Master of Science in Statistics and applied Probabilities at the National University of Singapore (NUS) .

Email / Scholar / Twitter / Github

News

03.2024 Our paper Grounding Everything: Emerging Localization Properties in Vision-Language Transformers was accepted at CVPR 2024!.

01.2024 I will be attending the BMVA Symposium on Vision and Language with an oral and a poster presenting our recent paper Grounding Everything.

Featured Research

	LeGrad: An Explainability Method for Vision Transformers via Feature Formation Sensitivity Walid Bousselham, Angie Boggust, Sofian Chaybouti Hendrik Strobelt Hilde Kuehne arXiv, 2024 Project Page / Code / arXiv / Demo
	Grounding Everything: Emerging Localization Properties in Vision-Language Transformers Walid Bousselham, Felix Petersen, Vittorio Ferrari, Hilde Kuehne CVPR, 2024 Code / arXiv / Demo
	Learning Situation Hyper-Graphs for Video Question Answering Aisha Urooj, Hilde Kuehne, Bo Wu, Kim Chheu, Walid Bousselham, Chuang Gan, Niels Lobo, Mubarak Shah CVPR, 2023 Code / arXiv
	Efficient Self-Ensemble for Semantic Segmentation Walid Bousselham, Guillaume Thibault, Lucas Pagano, Archana Machireddy, Joe Gray, Young Hwan Chang, Xubo Song BMVC, 2021 Code / arXiv / video

Design and source code borrowed from Jon Barron's website.