Shanshui Journey: Using AI to Reproduce the Experience of Chinese Literati Ink Paintings

Aven-Le Zhou; Kang Zhang

doi:10.1162/leon_a_02474

Shanshui Journey: Using AI to Reproduce the Experience of Chinese Literati Ink Paintings

Aven-Le Zhou
, Kang Zhang^*

^*Corresponding author for this work

The Hong Kong University of Science and Technology (Guangzhou)

Research output: Contribution to journal › Article › peer-review

5 Citations (Scopus)

Abstract

The authors investigate Chinese shanshui (literally, “mountain and water”), ink paintings of the natural landscape, through an interactive art installation entitled Shanshui Journey. By examining shanshui’s philosophy, multiple moving perspectives, and creation and appreciation practices, the work emphasizes motion in nature, memories, and interactive appreciation. These concepts are realized in a digitized room, where each participant’s motion is captured as a line “sketch” and transformed into an ink painting via a custom neural network. Generated paintings are displayed in real time alongside previous works, collectively termed Shanshui Memories, mimicking handscroll interaction. The authors’ approach to shanshui aims to reproduce the Chinese literati art experience, and to raise awareness of this cultural heritage.

Original language	English
Pages (from-to)	370-378
Number of pages	9
Journal	Leonardo
DOIs	https://doi.org/10.1162/leon_a_02474
Publication status	Published - 1 Aug 2024
Externally published	Yes

Access to Document

10.1162/leon_a_02474

5 Citations
2 Conference Proceeding

An interactive and generative approach for Chinese Shanshui painting document
Zhou, A. L., Wang, Q. F., Huang, K. & Lo, C. H., Sept 2019, Proceedings - 15th IAPR International Conference on Document Analysis and Recognition, ICDAR 2019. IEEE Computer Society, p. 819-824 6 p. 8978182. (Proceedings of the International Conference on Document Analysis and Recognition, ICDAR).
Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review
30 Citations (Scopus)
Walking Through Shanshui: Generating Chinese Shanshui Paintings via Real-time Tracking of Human Position
Zhou, A. L., Oct 2019, Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019. Institute of Electrical and Electronics Engineers Inc., p. 3185-3188 4 p. 9022422. (Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019).
Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review
2 Citations (Scopus)

1 Participating in an event e.g. a conference, workshop, …

Computer Vision Art Gallery
Zhou, A.-L. (Participant)
2 Nov 2019
Activity: Participating in or organising an event › Participating in an event e.g. a conference, workshop, …

Cite this

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title = "Shanshui Journey: Using AI to Reproduce the Experience of Chinese Literati Ink Paintings",

abstract = "The authors investigate Chinese shanshui (literally, “mountain and water”), ink paintings of the natural landscape, through an interactive art installation entitled Shanshui Journey. By examining shanshui{\textquoteright}s philosophy, multiple moving perspectives, and creation and appreciation practices, the work emphasizes motion in nature, memories, and interactive appreciation. These concepts are realized in a digitized room, where each participant{\textquoteright}s motion is captured as a line “sketch” and transformed into an ink painting via a custom neural network. Generated paintings are displayed in real time alongside previous works, collectively termed Shanshui Memories, mimicking handscroll interaction. The authors{\textquoteright} approach to shanshui aims to reproduce the Chinese literati art experience, and to raise awareness of this cultural heritage.",

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Shanshui Journey: Using AI to Reproduce the Experience of Chinese Literati Ink Paintings

Abstract

Access to Document

Research output

An interactive and generative approach for Chinese Shanshui painting document

Walking Through Shanshui: Generating Chinese Shanshui Paintings via Real-time Tracking of Human Position

Activities

Computer Vision Art Gallery

Cite this