18 citations · 58 across the 14 of their papers we have counts for
3 papers · 1 filter
PaDiM: a Patch Distribution Modeling Framework for Anomaly Detection and Localization
Thomas Defard, Aleksandr Setkov, Angelique Loesch +1
We present a new framework for Patch Distribution Modeling, PaDiM, to concurrently detect and localize anomalies in images in a one-class learning setting. PaDiM makes use of a pre…
Improving Few-Shot Learning through Multi-task Representation Learning Theory
Quentin Bouniot, Ievgen Redko, Romaric Audigier +2
In this paper, we consider the framework of multi-task representation (MTR) learning where the goal is to use source tasks to learn a representation that reduces the sample complex…
Unsupervised Domain Adaptation for Person Re-Identification through Source-Guided Pseudo-Labeling
Fabian Dubourvieux, Romaric Audigier, Angelique Loesch +2
Person Re-Identification (re-ID) aims at retrieving images of the same person taken by different cameras. A challenge for re-ID is the performance preservation when a model is used…