I am a Research Scientist at valeo.ai. I am working on deep learning and computer vision. I obtained a PhD in computer vision at Cnam under the superivion of Nicolas Thome (Sorbonne Université), Nicolas Audebert (IGN) and Clément Rambour (Cnam).

News

• I started at valeo.ai as a research scientist.
• Our paper for local prompt learning, GalLoP, was accepted to ECCV 2024.
• Our paper ITEM on improving the learning and evaluation of Message-Passing GNNs models in the recommendation task has been accepted at TMLR.
• I defended my PhD thesis on the 20th of March. I now officialy hold a PhD 🎉
• My pre-print submitted to TPAMI is now online; it contains the first of its kind hierarchical landmark retrieval dataset
• Our paper on OOD detection, HEAT, using energy-based models has been accepted to ICML 2023.
• Our paper on hierarchical image retrieval, HAPPIER, has been accepted to ECCV 2022.
• Our paper on ranking metric optimization for image retrieval, ROADMAP, has been accepted to NeurIPS 2021.

Publications

Robust and Decomposable Average Precision for Image Retrieval

Elias Ramzi, Nicolas Thome, Clément Rambour, Nicolas Audebert, Xavier Bitot: Robust and decomposable average precision for image retrieval. Advances in Neural Information Processing Systems 34 (NeurIPS, 2021).

Hierarchical Average Precision Training for Pertinent Image Retrieval

Elias Ramzi, Nicolas Audebert, Nicolas Thome, Clément Rambour, Xavier Bitot: RHierarchical Average Precision Training for Pertinent Image Retrieval. In: European Conference on Computer Vision. Springer (ECCV, 2022).

Hybrid Energy Based Model in the Feature Space for Out-of-Distribution Detection

Marc Lafon, Elias Ramzi, Clément Rambour, Nicolas Thome: Hybrid Energy Based Model in the Feature Space for Out-of-Distribution Detection. International Conference on Machine Learning (ICML 2023).

Optimization of Rank Losses for Image Retrieval

Elias Ramzi, Nicolas Audebert, Clément Rambour, André Araujo, Xavier Bitot, Nicolas Thome: Optimization of Rank Losses for Image Retrieval. Submitted to IEEE Transactions on Pattern Analysis and Machine Intelligence (under-review TPAMI).

GalLoP: Learning Global and Local Prompts for Vision-Language Models

Marc Lafon, Elias Ramzi, Clément Rambour, Nicolas Audebert, Nicolas Thome: GalLoP: Learning Global and Local Prompts for Vision-Language Models. European Conference on Computer Vision (ECCV 2024).