Neural-Symbolic Emotion-Pose Graph Reasoning in AI-Based Human Synthesis: A Multimodal Model Integrating Cognitive Priors—Digital Restoration of the Aesthetics of the Statue of Venus

This study aims to break through the traditional sculpture restoration paradigm centred on "geometric fitting", and proposes an aesthetic restoration framework that integrates emotion-gesture-symbol. Different from the geometric restoration that focuses on the symmetry of form and the fitting of points and lines, the aesthetic restoration emphasises the multi-dimensional linkage of emotional communication, dynamic aesthetics and cognitive consistency, and tries to restore the internal logic and sensual semantics of the "ideal beauty" in classical art works. In this paper, we introduce aesthetic cognitive a priori mapping for the first time, embed the emotional structure and visual semantics of classical sculptures into AI models, construct a neural-symbolic joint reasoning system, and integrate Transformer and graph neural network (GNN) to achieve cross-modal construction of gesture dynamics and expression generation. Through the experimental reconstruction of the eight restored versions of the Venus statue and typical postures such as the golden apple and the leaning pillar, combined with the quantitative indexes such as PCK, FID, Aesthetic Score, etc., we verified the model's performance in the areas of "perceptual proportions", "gesture dynamics", "props", and "expression generation". Combined with PCK, FID, Aesthetic Score and other quantitative indexes, it is verified that this model is superior to the traditional restoration path in terms of "perceptual proportion", "gesture and momentum", "props integration" and "divine expression". The study shows that aesthetic restoration is not only a reconstruction of the visual form, but also a deep cognitive reasoning process, and the results are more in line with the context of art history and the audience's perceptual experience. In the future, we will expand the temporal emotion modelling, historical archive enhancement mechanism and virtual reality immersive interaction, in order to promote the systematic application of AI in the fields of digital museums, art gallery restoration and cultural narrative generation.