Toward Embodied Collective Memory by Remediating Vernacular Photographs into Spatial Experience 38

This paper presents December 2022 Beijing , a VR work that remediates vernacular photographs of China’s COVID-19 reopening into embodied spatial encounters. It explores how the spatialization of fragmentary, private, and unevenly documented images can shift spectatorship from record-oriented viewing toward situated witnessing and reflection. The work spatializes vernacular photographs through single-image 3D Gaussian Splatting to construct immersive scenes. In cases where vernacular materials were unevenly recoverable, generative AI was used only as bounded inferential completion. Drawing on participant responses, the paper considers embodied re-encounter, empathy, and the low-fidelity aesthetic of 3D Gaussian Splatting as conditions for reflective, non-spectacular engagement.

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Publication Details

Journal
Proceedings of the ACM on Computer Graphics and Interactive Techniques
Published
2026-06-29
DOI
https://doi.org/10.1145/3816092
Primary Topic
Geographies of human-animal interactions
Type
article
Field-Weighted Citation Impact
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Toward Embodied Collective Memory by Remediating Vernacular Photographs into Spatial Experience 38

Zhigang Wang, MINZHI SHEN, 麦根, Yuan Zhang et al.
Proceedings of the ACM on Computer Graphics and Interactive Techniques
Geographies of human-animal interactions
article

Toward Embodied Collective Memory by Remediating Vernacular Photographs into Spatial Experience 38

Zhigang Wang, MINZHI SHEN, 麦根, Yuan Zhang, Wenbo Wang, Mengtai Zhang
article en

Abstract

This paper presents December 2022 Beijing , a VR work that remediates vernacular photographs of China’s COVID-19 reopening into embodied spatial encounters. It explores how the spatialization of fragmentary, private, and unevenly documented images can shift spectatorship from record-oriented viewing toward situated witnessing and reflection. The work spatializes vernacular photographs through single-image 3D Gaussian Splatting to construct immersive scenes. In cases where vernacular materials were unevenly recoverable, generative AI was used only as bounded inferential completion. Drawing on participant responses, the paper considers embodied re-encounter, empathy, and the low-fidelity aesthetic of 3D Gaussian Splatting as conditions for reflective, non-spectacular engagement.

Proceedings of the ACM on Computer Graphics and Interactive TechniquesVol. 9(3)
Tsinghua University (CN)
Openalex Percentile: Top 4%
Geographies of human-animal interactions
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