I am a PhD student in Computer Vision at Multimedia team (Telecom Paris) and VISTA team (LIX, École Polytechnique), supervised by Stéphane Lathuilière, Vicky Kalogeiton, and Slim Essid.
My PhD research focused on leveraging foundation models to advance generalization under distribution shift and limited supervision in semantic segmentation. I also interned at INRIA Paris in the Astra-vision team, where I worked on open-vocabulary semantic segmentation under the supervision of Raoul de Charette. I hold an engineering degree from École des Mines de Saint-Étienne and spent one year as an exchange student at EURECOM.
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Introduces a black-box distillation setting in which segmentation models specialize from closed API outputs, with no access to weights or logits. DINOv2 attention entropy is used to identify informative scales for pseudo-labeling unlabeled images.
Proposes a training-free method that uses prediction entropy to select per-class CLIP text templates, outperforming standard template averaging. As a plug-and-play module, it consistently boosts performance across open-vocabulary segmentation benchmarks.
Reviewing: I served as a reviewer for CVPR, ICCV, ECCV, NeurIPS and IJCV.
Teaching assistant: