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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) . |
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🔥 News05.2024 I spend the summer 2024 at MiT CSAIL as a visiting scholar working with Hendrik Strobelt and Angie Boggust. 05.2024 I gave a talk at "Cohere For AI - Community Talks" regarding our latest work "LeGrad" in collaboration with MiT & IBM Research. 03.2024 Our paper Grounding Everything: Emerging Localization Properties in Vision-Language Transformers was accepted at CVPR 2024!. 01.2024 I gave an interview to the Computer Vision News magazine, that features our recent paper "Grounding Everything". [Link to the interview] 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 |
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MaskInversion: Localized Embeddings via Optimization of Explainability Maps
Walid Bousselham, Sofian Chaybouti Christian Rupprecht, Vittorio Ferrari, Hilde Kuehne arXiv, 2024 Project Page / Code / arXiv |
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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 |
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Grounding Everything: Emerging Localization Properties in Vision-Language Transformers
Walid Bousselham, Felix Petersen, Vittorio Ferrari, Hilde Kuehne CVPR, 2024 Code / arXiv / Demo |
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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 |
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Efficient Self-Ensemble for Semantic Segmentation
Walid Bousselham, Guillaume Thibault, Lucas Pagano, Archana Machireddy, Joe Gray, Young Hwan Chang, Xubo Song BMVC, 2022 Code / arXiv / video |
🛠️ Open-source Libraries |
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MaskInversion
A library for generating localized embeddings of CLIP-like models via optimization of explainability maps. pip install maskinversion_torch
GitHub / PyPI |
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LeGrad
An explainability method for Vision Transformers that, given a text prompt, generates a heatmap localizing the part of the image that is important for the model to recognize the text prompt. pip install legrad_torch
GitHub / PyPI |
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GEM (Grounding Everything Method)
A library for exploring emerging localization properties in Vision-Language Transformers. pip install gem_torch
GitHub / PyPI |