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20202022
most citedPaDiM: a Patch Distribution Modeling Framework for Anomaly Detection and Localization

18 citations · 46 across the 6 of their papers we have counts for

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7 papers · 1 filter

cs.CV20229 cited

End-to-end Person Search Sequentially Trained on Aggregated Dataset

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) p…

cs.CV202210 cited

Describe me if you can! Characterized Instance-level Human Parsing

Angelique Loesch, Romaric Audigier

Several computer vision applications such as person search or online fashion rely on human description. The use of instance-level human parsing (HP) is therefore relevant since it…

cs.CV20222 cited

Detecting Human-to-Human-or-Object (H2O) Interactions with DIABOLO

Astrid Orcesi, Romaric Audigier, Fritz Poka Toukam +1

Detecting human interactions is crucial for human behavior analysis. Many methods have been proposed to deal with Human-to-Object Interaction (HOI) detection, i.e., detecting in an…

cs.CV20217 cited

Improving Unsupervised Domain Adaptive Re-Identification via Source-Guided Selection of Pseudo-Labeling Hyperparameters

Fabian Dubourvieux, Angélique Loesch, Romaric Audigier +2

Unsupervised Domain Adaptation (UDA) for re-identification (re-ID) is a challenging task: to avoid a costly annotation of additional data, it aims at transferring knowledge from a…

cs.CV202018 cited

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…

cs.CV2020

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…