Wafa Aissa

Attaché temporaire enseignement/recherche
Personal website:
Office: 37.1.40

I am a last-year Ph.D. student under the supervision of Michel Crucianu and Marin Ferecatu. The context of my PhD thesis is compositional visual reasoning. When presented with an image and a question pair, our objective is to have neural networks models answer the question by following a reasoning chain defined by a program. We assess the model's reasoning ability through a Visual Question Answering (VQA) setup. Compositional VQA breaks down complex questions into modular easier sub-problems. These sub-problems include reasoning skills such as object and attribute detection, relation detection, logical operations, counting, and comparisons. Each sub-problem is assigned to a different module. This approach discourages shortcuts, demanding an explicit understanding of the problem. It also promotes transparency and explainability.


Articles de conférence

  1. Aissa, W.; Ferecatu, M. and Crucianu, M. Curriculum Learning for Compositional Visual Reasoning. In Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, pages 888-897, Scitepress, Lisbon, Portugal, 2023. doi  www 
  1. Aissa, W.; Ferecatu, M. and Crucianu, M. Multimodal Representations for Teacher-Guided Compositional Visual Reasoning. In Advanced Concepts for Intelligent Vision Systems, 21st International Conference (ACIVS 2023), pages 357-369, Springer Nature, Kumamoto, Japan, Lecture Notes in Computer Science 14124, 2023. doi  www