3D Aesthetics is significant in digital design, shaping how users experience real-time 3D content in games, VR, and product design. However, creating aesthetically pleasing shapes remains challenging due to diverse subjective standards and the lack of tools that support aesthetics-driven editing. Users often rely on intuition without explicit guidance on visual appeal, making aesthetics refinement slow, inconsistent, and cognitively demanding, particularly in fast-paced, iterative workflows. To address this challenge, we conducted in-depth interviews with design experts to identify challenges in aesthetics-oriented modeling workflows. Based on the findings, we developed Aesthetic3D , a 3D modeling interface that provides real-time aesthetics scores learned from human perceptual data. Furthermore, Aesthetic3D seamlessly integrates the learned aesthetics measures into intuitive editing operations, enabling aesthetics-driven exploration and refinement of shape geometry. We evaluated Aesthetic3D through an ablation study, an open-ended study, and three generalization evaluations. Comprehensive experiments show that with Aesthetic3D , users can easily and effectively enhance the aesthetics appeal of 3D shapes.
Deng et al. (Fri,) studied this question.