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Ai-Assisted Sculpture Design

A Fusion of Tradition and Innovation

Bibliographic Data

ID22196204
AuthorsSubhash Kumar Verma (Noida International University), Sorabh Sharma (Chitkara University), Avishi Mohta (Vivekananda Global University), Rohit Chandwaskar (Parul University), Pompi Das Sengupta (National Institute of Technology Jamshedpur), Suma Sidramappa Hosamani (International Institute of Information Technology)
Year2025
Volume6
Issue5s
Pages173-183
Publication date2025-12-28
Open AccessYes
TypeARTICLE
VenueShodhKosh: Journal of Visual and Performing Arts (JOURNAL)
Journal identifiersISSN: 2582-7472 • E-ISSN: 2582-7472
PublisherGranthaalayah Publications and Printers (PUBLISHER • IN)
DOI10.29121/shodhkosh.v6.i5s.2025.6896
OpenAlexW7117671804
LanguageEN
References cited17

AI-assisted sculpture design is a radical melding of the conventional art craftsmanship and the innovative computational intelligence. The proposed study examines a hybrid form of creative ecosystem where sculptors work together with generative models, including GANs, diffusion systems, and mesh-generating neural networks to create sculptural, conceptually rich, structurally optimized, and culturally-infused sculptural entities. The suggested model will be based on the multimodal inputs which are hand-drawn sketches, 3D scans, material textures, and regional motifs which can allow the AI to be not only viewed as an automated tool but also as a collaborative contributor. Based upon the theories of human-machine collaboration and aesthetic cognition, the work presents how the concept of hybrid authorship redefines artistic intention, increases the speed of ideation, and facilitates experimentation with volumetric geometries that cannot be achieved in a field of manual work. The form of methodology is placed on the strict processing and annotation of sculptural data, native to curvature data, and surface anomalies, stylistic representation, and cultural emblem correlation. Moreover, a simulation layer of material consciousness is applied that assesses the reactions of stone, metals, clay, and composite, forecasts stressful regions, texture results, and manufacturability. The experiments show that there is a higher efficiency in design iteration, accuracy in integrating cultural motifs and physical plausibility of generated forms

Cirque · Consciousness · Creativity · Emblem · Generative grammar · Painting · Sculpture · Aesthetic Perception and Analysis · Art, Technology, and Culture · Music Technology and Sound Studies

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