Mitigating Intensity Bias in Shadow Detection via Feature Decomposition and Reweighting

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

29 Scopus Citations
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Detail(s)

Original languageEnglish
Title of host publicationProceedings - 2021 IEEE/CVF International Conference on Computer Vision
Subtitle of host publicationICCV 2021
PublisherIEEE
Pages4682-4691
ISBN (electronic)9781665428125
ISBN (print)9781665428132
Publication statusPublished - Oct 2021

Publication series

NameProceedings of the IEEE International Conference on Computer Vision
ISSN (Print)1550-5499
ISSN (electronic)2380-7504

Conference

Title18th IEEE/CVF International Conference on Computer Vision (ICCV 2021)
LocationVirtual
PlaceCanada
CityMontreal, QC
Period11 - 17 October 2021

Abstract

Although CNNs have achieved remarkable progress on the shadow detection task, they tend to make mistakes in dark non-shadow regions and relatively bright shadow regions. They are also susceptible to brightness change. These two phenomenons reveal that deep shadow detectors heavily depend on the intensity cue, which we refer to as intensity bias. In this paper, we propose a novel feature decomposition and reweighting scheme to mitigate this intensity bias, in which multi-level integrated features are decomposed into intensity-variant and intensity-invariant components through self-supervision. By reweighting these two types of features, our method can reallocate the attention to the corresponding latent semantics and achieves balanced exploitation of them. Extensive experiments on three popular datasets show that the proposed method outperforms state-of-the-art shadow detectors.

Bibliographic Note

Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).

Citation Format(s)

Mitigating Intensity Bias in Shadow Detection via Feature Decomposition and Reweighting. / Zhu, Lei; Xu, Ke; Ke, Zhanghan et al.
Proceedings - 2021 IEEE/CVF International Conference on Computer Vision: ICCV 2021. IEEE, 2021. p. 4682-4691 (Proceedings of the IEEE International Conference on Computer Vision).

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review