Understanding and Creating Art with AI: Review and Outlook

Cetinić, Eva; She, James

doi:10.1145/3475799

Cited by 193 publications

(94 citation statements)

References 109 publications

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“…Under the role of computer technology, images, colors, and other factors can form a multimedia three-dimensional information system through the collection, and this is the best expression of the multimedia nature of computer technology [24]. Under the influence of the multimedia of computer technology, fine art education can make many abstract and complicated artrelated teaching contents become concrete images through multimedia, so students' interest in art-related learning will be greatly enhanced, which can also change students' passive fine art learning in the past into active learning.…”

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confidence: 99%

The Application of Modern Computer-Aided Technology in Fine Art Education

Wang

2022

Security and Communication Networks

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With the popularization of modern computer technology, human society has stepped into the information age. Modern computer technology will have an all-round and deep impact on fine art education in China. In fine art education, various information devices play an important role in broadening the resources of fine art education and effectively improving the quality of fine art education. This study analyzes fine art education in the digital era and studies how the quality of fine art education can be improved through computer-aided technology.

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confidence: 99%

The Application of Modern Computer-Aided Technology in Fine Art Education

Wang

2022

Security and Communication Networks

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“…In recent years, there has been an increasing interest in applying Artificial Intelligence in the cultural heritage field [ 5 , 50 ]. Studies have been supported by the massive digitization of artworks and the release of public data sets.…”

Section: Related Workmentioning

confidence: 99%

Proposals Generation for Weakly Supervised Object Detection in Artwork Images

2022

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Object Detection requires many precise annotations, which are available for natural images but not for many non-natural data sets such as artworks data sets. A solution is using Weakly Supervised Object Detection (WSOD) techniques that learn accurate object localization from image-level labels. Studies have demonstrated that state-of-the-art end-to-end architectures may not be suitable for domains in which images or classes sensibly differ from those used to pre-train networks. This paper presents a novel two-stage Weakly Supervised Object Detection approach for obtaining accurate bounding boxes on non-natural data sets. The proposed method exploits existing classification knowledge to generate pseudo-ground truth bounding boxes from Class Activation Maps (CAMs). The automatically generated annotations are used to train a robust Faster R-CNN object detector. Quantitative and qualitative analysis shows that bounding boxes generated from CAMs can compensate for the lack of manually annotated ground truth (GT) and that an object detector, trained with such pseudo-GT, surpasses end-to-end WSOD state-of-the-art methods on ArtDL 2.0 (≈41.5% mAP) and IconArt (≈17% mAP), two artworks data sets. The proposed solution is a step towards the computer-aided study of non-natural images and opens the way to more advanced tasks, e.g., automatic artwork image captioning for digital archive applications.

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“…More importantly, our survey serves as the first effort of integrated reviews for two complementary facets of computational arts and the metaverse. To the best of our knowledge, the most relevant survey articles pinpoint either a focused area of computational arts, e.g., art collection analysis and AI-generated images [34] and media (video) intelligence [86], or fundamental developments of the metaverse, e.g., technological enablers and ecosystems of the metaverse [132], the metaverse applications and industry sectors [164], the design of virtual worlds and metaverse user perception [45]. In contrast, our survey paper aims to review the latest development of digital arts and investigate the potentials of computational arts in the metaverse era.…”

Section: Contributions Of the Surveymentioning

confidence: 99%

When Creators Meet the Metaverse: A Survey on Computational Arts

Lee

Lin²,

Hu³

et al. 2021

Preprint

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The metaverse, enormous virtual-physical cyberspace, has brought unprecedented opportunities for artists to blend every corner of our physical surroundings with digital creativity. This article conducts a comprehensive survey on computational arts, in which seven critical topics are relevant to the metaverse, describing novel artworks in blended virtual-physical realities. The topics first cover the building elements for the metaverse, e.g., virtual scenes and characters, auditory, textual elements. Next, several remarkable types of novel creations in the expanded horizons of metaverse cyberspace have been reflected, such as immersive arts, robotic arts, and other user-centric approaches fuelling contemporary creative outputs. Finally, we propose several research agendas: democratising computational arts, digital privacy and safety for metaverse artists, ownership recognition for digital artworks, technological challenges, and so on. The survey also serves as introductory material for artists and metaverse technologists to begin creations in the realm of surrealistic cyberspace.CCS Concepts: • Human-centered computing → Mixed / augmented reality; Graphical user interfaces; • Computing methodologies → Machine learning approaches.

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Understanding and Creating Art with AI: Review and Outlook

Cited by 193 publications

References 109 publications

The Application of Modern Computer-Aided Technology in Fine Art Education

The Application of Modern Computer-Aided Technology in Fine Art Education

Proposals Generation for Weakly Supervised Object Detection in Artwork Images

When Creators Meet the Metaverse: A Survey on Computational Arts

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