Domain Generalisation for Object Detection under Covariate and Concept Shift Article Swipe

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Karthik Seemakurthy , Charles W. Fox , Erchan Aptoula , Petra Bosilj ·

YOU? · · 2022 · Open Access · · DOI: https://doi.org/10.48550/arxiv.2203.05294

Domain generalisation aims to promote the learning of domain-invariant features while suppressing domain-specific features, so that a model can generalise better to previously unseen target domains. An approach to domain generalisation for object detection is proposed, the first such approach applicable to any object detection architecture. Based on a rigorous mathematical analysis, we extend approaches based on feature alignment with a novel component for performing class conditional alignment at the instance level, in addition to aligning the marginal feature distributions across domains at the image level. This allows us to fully address both components of domain shift, i.e. covariate and concept shift, and learn a domain agnostic feature representation. We perform extensive evaluation with both one-stage (FCOS, YOLO) and two-stage (FRCNN) detectors, on a newly proposed benchmark comprising several different datasets for autonomous driving applications (Cityscapes, BDD10K, ACDC, IDD) as well as the GWHD dataset for precision agriculture, and show consistent improvements to the generalisation and localisation performance over baselines and state-of-the-art.

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Domain (mathematical analysis) Computer science Object (grammar) Artificial intelligence Object detection Bounding overwatch Representation (politics) Pattern recognition (psychology) Invariant (physics) Consistency (knowledge bases) Minimum bounding box Feature (linguistics) Metadata Algorithm Image (mathematics) Mathematics Mathematical analysis Politics Operating system Political science Law Mathematical physics Linguistics Philosophy

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Type: preprint
Language: en
Landing Page: http://arxiv.org/abs/2203.05294
PDF: https://arxiv.org/pdf/2203.05294
OA Status: green
Cited By: 6
Related Works: 10
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DOI: https://doi.org/10.48550/arxiv.2203.05294

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Title: Domain Generalisation for Object Detection under Covariate and Concept Shift

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Type: preprint

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Language: en

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Publication year: 2022

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Publication date: 2022-03-10

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Authors: Karthik Seemakurthy, Charles W. Fox, Erchan Aptoula, Petra Bosilj

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Landing page: https://arxiv.org/abs/2203.05294

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Concepts: Domain (mathematical analysis), Computer science, Object (grammar), Artificial intelligence, Object detection, Bounding overwatch, Representation (politics), Pattern recognition (psychology), Invariant (physics), Consistency (knowledge bases), Minimum bounding box, Feature (linguistics), Metadata, Algorithm, Image (mathematics), Mathematics, Mathematical analysis, Politics, Operating system, Political science, Law, Mathematical physics, Linguistics, Philosophy

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Cited by: 6

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Citations by year (recent): 2025: 1, 2024: 1, 2023: 4

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abstract_inverted_index.different	129
abstract_inverted_index.extensive	111
abstract_inverted_index.features,	13
abstract_inverted_index.one-stage	115
abstract_inverted_index.precision	146
abstract_inverted_index.proposed,	35
abstract_inverted_index.two-stage	119
abstract_inverted_index.applicable	40
abstract_inverted_index.approaches	54
abstract_inverted_index.autonomous	132
abstract_inverted_index.components	93
abstract_inverted_index.comprising	127
abstract_inverted_index.consistent	150
abstract_inverted_index.detectors,	121
abstract_inverted_index.evaluation	112
abstract_inverted_index.generalise	19
abstract_inverted_index.performing	64
abstract_inverted_index.previously	22
abstract_inverted_index.conditional	66
abstract_inverted_index.performance	157
abstract_inverted_index.suppressing	11
abstract_inverted_index.(Cityscapes,	135
abstract_inverted_index.agriculture,	147
abstract_inverted_index.applications	134
abstract_inverted_index.improvements	151
abstract_inverted_index.localisation	156
abstract_inverted_index.mathematical	50
abstract_inverted_index.architecture.	45
abstract_inverted_index.distributions	79
abstract_inverted_index.generalisation	1, 30, 154
abstract_inverted_index.domain-specific	12
abstract_inverted_index.representation.	108
abstract_inverted_index.domain-invariant	8
abstract_inverted_index.state-of-the-art.	161
cited_by_percentile_year
countries_distinct_count	0
institutions_distinct_count	4
sustainable_development_goals[0].id	https://metadata.un.org/sdg/11
sustainable_development_goals[0].score	0.5199999809265137
sustainable_development_goals[0].display_name	Sustainable cities and communities
citation_normalized_percentile