Open research questions in Aesthetic Perception and Analysis
247 unresolved questions extracted from the limitations and future-work sections of 1,765 Aesthetic Perception and Analysis papers in our library. Each links back to the study that raised it.
What the literature leaves open
The challenge of connecting a modern artistic glyph to its potential evolutionary precursors. The difficulty of distinguishing the pictorial style and character style in character art. The need to provide historical grounding and stylistic understanding in the analysis of character art.
The framework does not attempt to semantically decipher the glyphs. The standard mLLMs lack historical groundings and are hard to distinguish the pictorial style and character style. The models are trained on broad web-scale data and function as highly capable generalists.
The extent to which there can be such a thing as a significant relation between the aesthetic and understanding is still a controversial question. Aesthetic experience is often seen as separate from cognitive processes. The paper argues that the cognitive complexity of aesthetic experience is generally understated.
The technical challenges of encoding complex emotions into visual forms. The difficulty of translating the nuanced spectrum of human emotions into AI-generated imagery. The need for more advanced AI models that can more finely understand and reflect the complexity of human emotions.
exploring the use of deep learning and neural networks to enhance AI's capability in emotion, - investigating the impact of AI-generated architectural imagery on other populations, - examining the effects of different AI models on emotional expression
Although art viewing can enhance wellbeing, the effects of embodied interaction, particularly the interplay between artwork scale and locomotion, on the psychological and behavioral dimensions of VR experiences remain understudied.
As AI-driven creativity advances, future research should focus on making things easier to understand, reducing biases in algorithms, and refining the ways in which humans and AI work together to create new things.
Abstract The processes by which traditional artistic knowledge is transmitted across generations with high fidelity remain poorly understood, particularly in non-Western contexts.
However, it remains unclear exactly which features of art knowledge shape understanding and thinking.
Art knowledge training shapes understanding, inspires creativity and stimulates thinking · 2026 · DOIThe relationship between understanding and aesthetic appraisal in mathematics is an open question, with implications for both the philosophy of mathematics and mathematics education.
These findings challenge the view that aesthetic judgements in mathematics are merely disguised epistemic judgements, and suggest that future research should focus on exploring the non-epistemic factors that shape aesthetic judgements.
Despite this intriguing possibility, limited research has systematically examined these differences.
Comparative analysis of color emotional perception in art and non-art university students: hue, saturation, and brightness effects in the Munsell color system · 2025 · DOIHowever, the influence of artistic training on color perception and neural processing remains poorly understood.
Electroencephalographic (EEG) analysis of hue perception differences between art and non-art majors: insights from the P2 and P3 components · 2025 · DOIMuch more remains to be told, especially the stories of the other two conversations about the outside of women's bodies, dance and fashion, and of how they, along with beauty culture, achieved both legitimacy and widespread popularity through the modern technologies of radio, cinema, and mass journalism.
The paper suggests future research prospects of immersive and interactive systems based on AI using creativity. The paper outlines the future research directions of using generative AI to integrate into artistic space.
ARTIFICIAL INTELLIGENCE AS A CREATIVE COLLABORATOR IN CONTEMPORARY VISUAL AND PERFORMING ARTS · 2026 · DOIThe lack of understanding of how AI can be used to support artists in the design and exploration of the artistic process. The need for a framework that integrates information preparation, generative models, human-AI interaction, and rendering to create a creative pipeline in collaboration.
ARTIFICIAL INTELLIGENCE AS A CREATIVE COLLABORATOR IN CONTEMPORARY VISUAL AND PERFORMING ARTS · 2026 · DOIThe gap between human and machine creativity is becoming more and more indistinct. There is a need to discuss the changing argument over authorship in AI-generated art.
Table 2 shows that final artwork selection has 86% perceived authorship score (highest human influence), but the paper does not examine whether this perception varies across different demographic groups, artistic expertise levels, or cultural backgrounds. The generalizability of authorship perception findings across diverse human evaluators requires investigation.
The future of cultural analytics in visual arts research will be shaped by emerging technologies. The combination of multimodal data sources, including textual metadata and visual images, can provide new insights into the cultural and historical context of artistic movements.
The study identifies a gap in the use of traditional methods to analyze visual arts. The lack of quantitative analysis of aesthetic trends in visual arts is discussed.
The study identifies a gap in our understanding of the relationship between human creativity and artificial intelligence. The paper highlights the need for a deeper understanding of the cognitive risks associated with the hybridization of the creative process.
Limited research has examined how specific design dimensions influence consumer purchase behavior in museum contexts. Existing studies largely operationalize value as a general construct without clearly linking specific product attributes to distinct value dimensions.
A Conceptual Framework on Decomposing Design Perception into Functional, Color, and Shape Effects on Purchase Behavior of Museum Cultural Products · 2026 · DOIThe paper identifies a gap in the existing literature on digital art and interactivity. The study highlights the need for further research on the role of digital brushstrokes in creating a new form of artistic expression. The paper notes that there is a lack of understanding of the relationship between interactivity and viewer engagement in the context of digital brushstroke art.
Digital brushstrokes: merging art, technology, and interactivity in the age of digital media · 2026 · DOIExisting benchmarks adopt only one annotation protocol, leaving their complementarity unmeasured. There is a need for a dual-protocol benchmark that combines pairwise preferences and pointwise ratings.
Preferences Order, Ratings Anchor: From Fused Expert Aesthetic Ground Truth to Self-Distillation · 2026The lack of systematic research and cross-domain innovation in the digitalization of traditional oriental folk art. The insufficient applications of AIGC technology in the field of oriental folk art patterns.
Transformation of artistic style and innovative design of oriental folk patterns based on AIGC Technology—A case study of Zhuxian town new year paintings from China · 2026 · DOI
Most-cited papers in Aesthetic Perception and Analysis
- A model of aesthetic appreciation and aesthetic judgments · British Journal of Psychology · 2004 · 1,453 citations
- Atmosphere as the Fundamental Concept of a New Aesthetics · Thesis Eleven · 1993 · 629 citations
- Understanding and Creating Art with AI: Review and Outlook · ACM Transactions on Multimedia Computing Communications and Applications · 2022 · 459 citations
- Speaking of Art as Embodied Imagination: A Multisensory Approach to Understanding Aesthetic Experience · Journal of Consumer Research · 2003 · 430 citations
- Ten years of a model of aesthetic appreciation and aesthetic judgments : The aesthetic episode – Developments and challenges in empirical aesthetics · British Journal of Psychology · 2014 · 406 citations
- Effects of external evaluation on artistic creativity. · Journal of Personality and Social Psychology · 1979 · 376 citations
- Generative artificial intelligence, human creativity, and art · PNAS Nexus · 2024 · 363 citations
- Accuracy of digital and conventional impression techniques and workflow · Clinical Oral Investigations · 2012 · 289 citations
- Finding Form: Looking at the Field of Organizational Aesthetics · Journal of Management Studies · 2005 · 284 citations
- Neuroscience of aesthetics · Annals of the New York Academy of Sciences · 2016 · 270 citations
Most recent work
- A Pluralist Perspective on Shape Constancy · The British Journal for the Philosophy of Science · 2026
- Advancing the generation and integration of traditional motifs through AI-based techniques · Discover Artificial Intelligence · 2026
- Effects of adaptation to altered color statistics provide evidence for calibration of color perception to the color statistics of natural scenes. · Journal of Experimental Psychology General · 2026
- A design-integrated framework for neuroarchitectural research · Frontiers in Psychology · 2026
- Why Are Consumers Ambivalent About AI ‐Generated Images? The Moderating Role of Commercial Versus Noncommercial Content Type · Journal of Consumer Behaviour · 2026
- Tracing the epistemic arc: Distinct physiological signatures for curiosity, insight, understanding and liking when viewing visual art · bioRxiv · 2026
- Art knowledge training shapes understanding, inspires creativity and stimulates thinking · Royal Society Open Science · 2026
- When algorithms plate: Can AI-generated aesthetics rival reality? · International Journal of Gastronomy and Food Science · 2026
- Neural dynamics of aesthetic appreciation: fNIRS evidence from poetry reading · NeuroImage · 2026
- "There is Beauty in the Small": A Study of Visual Artists’ Impressions of Small Data and Model Crafting Approaches to Creative AI Work · 2026
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