1 code implementation • 10 Nov 2023 • Remi Marsal Florian Chabot, Angelique Loesch, William Grolleau, Hichem Sahbi
Self-supervised monocular depth estimation methods aim to be used in critical applications such as autonomous vehicles for environment analysis.
no code implementations • 24 Jan 2022 • Angelique Loesch, Jaonary Rabarisoa, Romaric Audigier
In video surveillance applications, person search is a challenging task consisting in detecting people and extracting features from their silhouette for re-identification (re-ID) purpose.
no code implementations • 24 Jan 2022 • Angelique Loesch, Romaric Audigier
In addition, we propose HPTR, a new bottom-up multi-task method based on transformers as a fast and scalable baseline.
22 code implementations • 17 Nov 2020 • Thomas Defard, Aleksandr Setkov, Angelique Loesch, Romaric Audigier
We present a new framework for Patch Distribution Modeling, PaDiM, to concurrently detect and localize anomalies in images in a one-class learning setting.
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no code implementations • 20 Sep 2020 • Fabian Dubourvieux, Romaric Audigier, Angelique Loesch, Samia Ainouz, Stephane Canu
A challenge for re-ID is the performance preservation when a model is used on data of interest (target data) which belong to a different domain from the training data domain (source data).