Surprising Image Compositions

Othman Sbai, Camille Couprie, Mathieu Aubry

CVPRW 2021 pp. 3926-3930

doi:10.1109/CVPRW53098.2021.00438 /cvprw/2021/sbai2021cvprw-surprising/

Abstract

Visual metaphors are a powerful and effective way of communication in advertising, news, and art. By taking objects out of their natural context, artists create new and surprising composite images by leveraging visual, linguistic, or phonetic analogies. We build on recent image retrieval, completion and composition methods to design a new collage generation tool with the aim of assisting artists in creating interesting composite images. Given a selected object in an image, our model searches for visually similar but semantically different objects and performs the image blending automatically, leading to surprising image combinations. Using automatic metrics and a human study, we test our approach against baselines and show the potential of this novel artistic application.

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Cite

Text

Sbai et al. "Surprising Image Compositions." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2021. doi:10.1109/CVPRW53098.2021.00438

Markdown

[Sbai et al. "Surprising Image Compositions." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2021.](https://mlanthology.org/cvprw/2021/sbai2021cvprw-surprising/) doi:10.1109/CVPRW53098.2021.00438

BibTeX

@inproceedings{sbai2021cvprw-surprising,
  title     = {{Surprising Image Compositions}},
  author    = {Sbai, Othman and Couprie, Camille and Aubry, Mathieu},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2021},
  pages     = {3926-3930},
  doi       = {10.1109/CVPRW53098.2021.00438},
  url       = {https://mlanthology.org/cvprw/2021/sbai2021cvprw-surprising/}
}