Positions & Visits

Research Interests & Applications

Methodology

Deep Learning & Generative Modeling: Flow-based models, stable invertible networks.

Statistical ML: Deep kernels, Graph Convolutional Networks (GCNs).

Optimization: Label-efficient/Continual learning, network compression/pruning.

Applications

  • Autonomous Driving (Scene/Optical Flow)
  • Action Recognition (Skeleton/Visual Speech)
  • Remote Sensing (Satellite Image Change Detection)
  • 3D/4D Point Cloud Modeling

Awards & Recognition

ORGANIZING-COMMITTEES, MEMBERSHIPS, SCIENTIFIC AND ADMINISTRATIVE RESPONSIBILITIES

Editorial Boards

Organization Assistance and Conference Memberships

Sessions Chairing

Committees & Responsibilities

Selected Publications (Rank A*/A conferences) + Major Journals

Y. Huang, J. Mei, Z. Wu, Y. Yang, H. Zhao, M. Jiu, H. Sahbi. Less Is Better: Sparse Instance Learning for Cross-Domain Few-Shot Object Detection. In the 40th Annual AAAI Conference on Artificial Intelligence (AAAI). 2026. [Link]
V. Enescu, H. Sahbi. Learning conditionally untangled latent spaces using Fixed Point Iteration. In the 35th British Machine Vision Conference (BMVC). 2024. [Link]
R. Marsal, F. Chabot, A. Loesch, W. Grolleau, H. Sahbi. MonoProb: Self-Supervised Monocular Depth Estimation with Interpretable Uncertainty. In WACV. 2024. [Link]
R. Marsal, F. Chabot, A. Loesch, H. Sahbi. BrightFlow: Brightness-Change-Aware Unsupervised Learning of Optical Flow. In WACV. 2023. [Link]
M. Jiu and H. Sahbi. Context-Aware Deep Kernel Networks for Image Annotation. In Neurocomputing Journal. 2022. [Link]
H. Sahbi. Learning Laplacians in Chebyshev Graph Convolutional Networks. In ICCV, DLGC. 2021. [Link]
H. Sahbi and H. Zhan. FFNB: Forgetting-Free Neural Blocks for Deep Continual Learning. In BMVC. 2021. [Link]
A. Mazari and H. Sahbi. MLGCN: Multi-Laplacian Graph Convolutional Networks for Human Action Recognition. In BMVC. 2019. [Link]
A. Dutta and H. Sahbi. Stochastic Graphlet Embedding. In IEEE Transactions on Neural Networks and Learning Systems (TNNLS). 2019. [Link]
M. Jiu and H. Sahbi. Nonlinear Deep Kernel Learning for Image Annotation. In IEEE Transactions on Image Processing (TIP). 2017. [Link]
H. Sahbi. Interactive Satellite Image Change Detection with Context-Aware Canonical Correlation Analysis. In IEEE GRSL. 2017. [Link]
L. Wang and H. Sahbi. Directed Acyclic Graph Kernels for Action Recognition. In ICCV. 2013. [Link]
H. Sahbi, L. Ballan, G. Serra, A. Del Bimbo. Context-Dependent Logo Matching and Recognition. In IEEE TIP. 2013. [Link]
P-D. Vo, H. Sahbi. Spacious: an Interactive Mental Search Interface. In ACM SIGIR. 2013. [Link]
F. Yuan, G-S. Xia, H. Sahbi and V. Prinet. Mid-level Features and Spatio-Temporal Context for Activity Recognition. In Pattern Recognition. 2012. [Link]
H. Sahbi, J-Y. Audibert and R. Keriven. Context-Dependent Kernels for Object Classification. In IEEE PAMI. 2011. [Link]
H. Sahbi and X. Li. Context Based Support Vector Machines for Interconnected Image Annotation. The Saburo Tsuji Best Paper Award In ACCV. 2010. [Link]
H. Sahbi and X. Li. Context Dependent SVMs for Interconnected Image Network Annotation. In ACM Multimedia. 2010. [Link]
H. Sahbi, J-Y. Audibert, J. Rabarisoa and R. Keriven. Robust Matching and Recognition using Context-Dependent Kernels. In ICML. 2008. [Link]
H. Sahbi, P. Etyngier, J-Y Audibert and R. Keriven. Manifold Learning using Robust Graph Laplacian for Interactive Image Retrieval. In CVPR. 2008. [Link]
H. Sahbi, J-Y. Audibert, J. Rabarisoa and R. Keriven. Context-Dependent Kernel Design for Object Matching and Recognition. In CVPR. 2008. [Link]
H. Sahbi, J-Y Audibert and R. Keriven. Graph-Cut Transducers for Relevance feedback in Content Based Image Retrieval. In ICCV. 2007. [Link]
H. Sahbi. Kernel PCA for Similarity Invariant Shape Recognition. In Neurocomputing Journal. 2007. [Link]
H. Sahbi and D. Geman. A Hierarchy of Support Vector Machines for Face Detection. In JMLR. 2006. [Link]

All Publications: [Google Scholar] [DBLP]

Past and Current Projects

Supervision & Mentoring

Supervised PhD Students (as Thesis Director)

Supervised Post-Docs (as Official Postdoc Director)

Co-Supervised & Visiting Students (Only as Co-supervisor)

Biosketch