Smart vision

  • Head: Achraf Ben-Hamadou
  • Field: Computer vision, machine learning
  • Theme: Data-drive models for computer vision, 3D vision

Team presentation

Smart vision is a highly motivated team working on challenging computer vision/machine learning problems related to different front-end applications like augmented/virtual reality, human-machine interaction, biometrics and video-surveillance, scene understanding, etc.

Research activities

Our current research activities are mainly focused on designing data-driven methods for computer vision. Nowadays, there is an abundance of data that can be used to learn models serving computer vision applications. Learning data could be obtained using faithfull simulators, from available image/video data on Internet, or from already annotated big datasets. With the latest progress in machine learning techniques and computing efficiency, data-driven methods became a strong research trend.


3D reconstruction 2D/3D pose prediction and tracking SLAM Deep learning 2D/3D object detection Augmented/Virtual Reality Human Face Analysis LiDAR/Image data fusion

Team members

  • Achraf Ben-Hamadou, Assistant professor
  • Ahmed Rekik, Assistant professor
  • Houda Chaabouni-Chouayakh, PostDoc researcher
  • Nesrine Masmoudi, PostDoc researcher
  • Nessrine Grati, PhD student
  • Samar Daou, PhD student
  • Abderraouf Guesmi, PhD student
  • Nour Neifar, PhD student
  • Mohamed Firas Bouzguenda, Engineer intern
  • Mohamed Hedi Turki, Engineer intern
  • Khaled chenguel, Engineer intern
  • Mahdi Mseddi, Engineer intern
  • Oussama Belhadj Slimeni, Engineer intern
  • Yassine Timoumi, Engineer intern
  • Oussama Smaoui, Engineer inter


  • Mohamed Hammami, Associate professor, Miracl laboratory
  • Walid Mahdi, Professor, Miracl laboratory
  • Abdeaziz Kallel, Associate professor, CRNS