Hasil untuk "Arts in general"

Doris Hambuch, Moza Al Tenaijy, Aisha Khamis Aldarmaki et al.

This study investigates the motivations of Emirati creative writers to choose the global language, English, rather than the UAE’s official language, Arabic, for their literary texts. Much scholarship has been dedicated to the role of English in the Gulf region, but hardly any of this research focusses on the arts. Drawing upon studies of anglophone literature from other countries where English is not an official language, content analysis, and a case study, this article identifies the reach for international audiences as the main motivation, followed by personal language command. Literary influence and genre selection are minor reasons causing Emirati writers to published in English. Situating the small but steadily growing translingual, or exophonic Emirati canon within the short local literary history as well as within a global anglophone context, the article also demonstrates that innovative uses of language may occur. Regional efforts to promote local authors along with changing publishing conditions will likely lead to an expansion of the studied canon in the near future.

Staas de Jong, Gerrit van der Veer

The retinal afterimage is a widely known effect in the human visual system, which has been studied and used in the context of a number of major art movements. Therefore, when considering the general role of computation in the visual arts, this begs the question whether this effect, too, may be induced using partly automated techniques. If so, it may become a computationally controllable ingredient of (interactive) visual art, and thus take its place among the many other aspects of visual perception which already have preceded it in this sense. The present moment provides additional inspiration to lay the groundwork for extending computer graphics in general with the retinal afterimage: Historically, we are in a phase where some head-mounted stereoscopic AR/VR technologies are now providing eye tracking by default, thereby allowing realtime monitoring of the processes of visual fixation that can induce the retinal afterimage. A logical starting point for general investigation is then shape display via the retinal afterimage, since shape recognition lends itself well to unambiguous reporting. Shape recognition, however, may also occur due to normal vision, which happens simultaneously. Carefully and rigorously excluding this possibility, we develop computational techniques enabling shape display exclusive to the retinal afterimage.

Shuai Wang, Ivona Najdenkoska, Hongyi Zhu et al.

Understanding visual art requires reasoning across multiple perspectives -- cultural, historical, and stylistic -- beyond mere object recognition. While recent multimodal large language models (MLLMs) perform well on general image captioning, they often fail to capture the nuanced interpretations that fine art demands. We propose ArtRAG, a novel, training-free framework that combines structured knowledge with retrieval-augmented generation (RAG) for multi-perspective artwork explanation. ArtRAG automatically constructs an Art Context Knowledge Graph (ACKG) from domain-specific textual sources, organizing entities such as artists, movements, themes, and historical events into a rich, interpretable graph. At inference time, a multi-granular structured retriever selects semantically and topologically relevant subgraphs to guide generation. This enables MLLMs to produce contextually grounded, culturally informed art descriptions. Experiments on the SemArt and Artpedia datasets show that ArtRAG outperforms several heavily trained baselines. Human evaluations further confirm that ArtRAG generates coherent, insightful, and culturally enriched interpretations.

Julien Gachadoat, Guillaume Lagarde

Generative art systems often involve high-dimensional and complex parameter spaces in which aesthetically compelling outputs occupy only small, fragmented regions. Because of this combinatorial explosion, artists typically rely on extensive manual trial-and-error, leaving many potentially interesting configurations undiscovered. In this work we make two contributions. First, we introduce ParamExplorer, an interactive and modular framework inspired by reinforcement learning that helps the exploration of parameter spaces in generative art algorithms, guided by human-in-the-loop or even automated feedback. The framework also integrates seamlessly with existing p5js projects. Second, within this framework we implement and evaluate several exploration strategies, referred to as agents.

In Gim, Zhiyao Ma, Seung-seob Lee et al.

Emerging large language model (LLM) applications involve diverse reasoning strategies and agentic workflows, straining the capabilities of existing serving systems built on a monolithic token generation loop. This paper introduces Pie, a programmable LLM serving system designed for flexibility and efficiency. Pie decomposes the traditional generation loop into fine-grained service handlers exposed via an API and delegates control of the generation process to user-provided programs, called inferlets. This enables applications to implement new KV cache strategies, bespoke generation logic, and seamlessly integrate computation and I/O-entirely within the application, without requiring modifications to the serving system. Pie executes inferlets using WebAssembly, benefiting from its lightweight sandboxing. Our evaluation shows Pie matches state-of-the-art performance on standard tasks (3-12% latency overhead) while significantly improving latency and throughput (1.3x-3.4x higher) on agentic workflows by enabling application-specific optimizations.

Sai Coumar, Zachary Kingston

Generating structured ASCII art using computational techniques demands a careful interplay between aesthetic representation and computational precision, requiring models that can effectively translate visual information into symbolic text characters. Although Convolutional Neural Networks (CNNs) have shown promise in this domain, the comparative performance of deep learning architectures and classical machine learning methods remains unexplored. This paper explores the application of contemporary ML and DL methods to generate structured ASCII art, focusing on three key criteria: fidelity, character classification accuracy, and output quality. We investigate deep learning architectures, including Multilayer Perceptrons (MLPs), ResNet, and MobileNetV2, alongside classical approaches such as Random Forests, Support Vector Machines (SVMs) and k-Nearest Neighbors (k-NN), trained on an augmented synthetic dataset of ASCII characters. Our results show that complex neural network architectures often fall short in producing high-quality ASCII art, whereas classical machine learning classifiers, despite their simplicity, achieve performance similar to CNNs. Our findings highlight the strength of classical methods in bridging model simplicity with output quality, offering new insights into ASCII art synthesis and machine learning on image data with low dimensionality.

اعظم لرنی, ناهید اکبری, ابراهیم ابراهیم تبار et al.

سیمین بهبهانی ازجمله شاعران معاصر است که شعرش از همان آغاز شاعری صبغه‌ای واقع‌گرایانه داشت و به واقعیات تلخ، غم‌انگیز و حتی نفرت‌آور اجتماع توجه نشان می‌داد. با نگاهی به سروده‌های او در مجموعه‌های «جای پا»، «چلچراغ»، «مرمر» و «رستاخیز» به روشنی می‌توان دریافت که در همۀ این آثار او تلاش می‌کند تا واقعیت را به تصویر بکشد. از این‌رو، شعر سیمین نمایان‌گر مؤلفه‌ها و نمودهای همه‌جانبه آثار رئالیستی و ناتورالیستی است. لذا پژوهش حاضر به روش توصیفی و ‌تحلیلی به بررسی این موضوع در شعر بهبهانی پرداخته است. یافته‌های این پژوهش نشان می‌دهد که حضور شخصیت‌های رئال و واقعی در شعر او (مانند: روسپی، دلقک، گورکن، جیب‌بر، کارگر، کارمند و مردم فقیر)، زنان، دغدغه‌ها و مسائل اجتماعی زندگی آنان، فقر در جامعه و رنج‌ها و دردهای مردمان، همچنین به‌کارگیری زبان عامیانه که موجب سادگی و روانی زبان شعری سیمین شده، ازجمله ویژگی‌های رئالیستی در آثار اوست. از سوی دیگر، رئالیسم و ناتورالیسم در نقاشی معاصر ایران نیز نمود واضحی دارد.اهداف پژوهش:بررسی رئالیسم و ناتورالیسم در شعر سیمین بهبهانیبررسی رئالیسم و ناتورالیسم در نقاشی معاصر ایران.سؤالات پژوهش:مؤلفه‌های رئالیستی و ناتورالیستی چگونه در اشعار سیمین بهبهانی جلوه‌گر شده است؟رئالیسم و ناتورالیسم در نقاشی معاصر ایران چگونه بازتاب یافته است؟

Diogo Nunes

Uma Flor da Vida Para o Recordar’ é um projeto artístico que resultou numa obra de arte que ficará instalada em permanência na Assembleia da Républica Portuguesa. Procurando uma abordagem consciente em relação ao seu lugar de implementação, considera de forma crítica as obras artísticas presentes no edifício no contexto do Pós-Colonialismo Português, especialmente o mural do pintor Domingos Rebelo, que mostra o “descobridor” Vasco da Gama a ser recebido pelos “emissários” de Samorim. Esta, faz o upcycling através da arte de sete modelos de cinzeiros cerâmicos cedidos pelo Parlamento português após deixarem de servir a sua função de ofertas institucionais. Para isto propomos o conceito de object-specific como ideia orientadora para subverter o papel anterior dos cinzeiros como lugares do apagar, do descartar e do esquecer de histórias normalmente ignoradas sob o sistema de sedução que envolve a comudidade capitalista. A fim de contrariar ontologias do capitaloceno, procurou-se desvendar um vislumbre do seu Kainos no Rizhoma representando momentos históricos da relação da sociedade ocidental com o tabaco através da primeira pintura cerâmica que representa uma folha de tabaco, momentos cruciais na sua disseminação na cultura e mercados ocidentais assim como os seus impactos socio-ambientais atuais. Finalmente será partilhado brevemente o processo de aprovisionamento para e produção do projeto. Esta contou com a elaboração quer de uma estrutura em perfis de plástico reciclado na mesma zona metropolitana da sua produção quer a pintura pós-vidrado dos cinzeiros.

Mar Canet Sola, Varvara Guljajeva

This paper explores the potential of generative AI within interactive art, employing a practice-based research approach. It presents the interactive artwork "Visions of Destruction" as a detailed case study, highlighting its innovative use of generative AI to create a dynamic, audience-responsive experience. This artwork applies gaze-based interaction to dynamically alter digital landscapes, symbolizing the impact of human activities on the environment by generating contemporary collages created with AI, trained on data about human damage to nature, and guided by audience interaction. The transformation of pristine natural scenes into human-made and industrialized landscapes through viewer interaction serves as a stark reminder of environmental degradation. The paper thoroughly explores the technical challenges and artistic innovations involved in creating such an interactive art installation, emphasizing the potential of generative AI to revolutionize artistic expression, audience engagement, and especially the opportunities for the interactive art field. It offers insights into the conceptual framework behind the artwork, aiming to evoke a deeper understanding and reflection on the Anthropocene era and human-induced climate change. This study contributes significantly to the field of creative AI and interactive art, blending technology and environmental consciousness in a compelling, thought-provoking manner.

Yuying Li, Zeyan Liu, Junyi Zhao et al.

Generative AI models can produce high-quality images based on text prompts. The generated images often appear indistinguishable from images generated by conventional optical photography devices or created by human artists (i.e., real images). While the outstanding performance of such generative models is generally well received, security concerns arise. For instance, such image generators could be used to facilitate fraud or scam schemes, generate and spread misinformation, or produce fabricated artworks. In this paper, we present a systematic attempt at understanding and detecting AI-generated images (AI-art) in adversarial scenarios. First, we collect and share a dataset of real images and their corresponding artificial counterparts generated by four popular AI image generators. The dataset, named ARIA, contains over 140K images in five categories: artworks (painting), social media images, news photos, disaster scenes, and anime pictures. This dataset can be used as a foundation to support future research on adversarial AI-art. Next, we present a user study that employs the ARIA dataset to evaluate if real-world users can distinguish with or without reference images. In a benchmarking study, we further evaluate if state-of-the-art open-source and commercial AI image detectors can effectively identify the images in the ARIA dataset. Finally, we present a ResNet-50 classifier and evaluate its accuracy and transferability on the ARIA dataset.

Linmi Tao, Ruiyang Liu, Donglai Tao et al.

Numerical difference computation is one of the cores and indispensable in the modern digital era. Tao general difference (TGD) is a novel theory and approach to difference computation for discrete sequences and arrays in multidimensional space. Built on the solid theoretical foundation of the general difference in a finite interval, the TGD operators demonstrate exceptional signal processing capabilities in real-world applications. A novel smoothness property of a sequence is defined on the first- and second TGD. This property is used to denoise one-dimensional signals, where the noise is the non-smooth points in the sequence. Meanwhile, the center of the gradient in a finite interval can be accurately location via TGD calculation. This solves a traditional challenge in computer vision, which is the precise localization of image edges with noise robustness. Furthermore, the power of TGD operators extends to spatio-temporal edge detection in three-dimensional arrays, enabling the identification of kinetic edges in video data. These diverse applications highlight the properties of TGD in discrete domain and the significant promise of TGD for the computation across signal processing, image analysis, and video analytic.

Anne-Sofie Maerten, Derya Soydaner

This paper delves into the fascinating field of AI-generated art and explores the various deep neural network architectures and models that have been utilized to create it. From the classic convolutional networks to the cutting-edge diffusion models, we examine the key players in the field. We explain the general structures and working principles of these neural networks. Then, we showcase examples of milestones, starting with the dreamy landscapes of DeepDream and moving on to the most recent developments, including Stable Diffusion and DALL-E 3, which produce mesmerizing images. We provide a detailed comparison of these models, highlighting their strengths and limitations, and examining the remarkable progress that deep neural networks have made so far in a short period of time. With a unique blend of technical explanations and insights into the current state of AI-generated art, this paper exemplifies how art and computer science interact.

Sharon Chokuwa, Muhammad H. Khan

Domain generalization for Diabetic Retinopathy (DR) classification allows a model to adeptly classify retinal images from previously unseen domains with various imaging conditions and patient demographics, thereby enhancing its applicability in a wide range of clinical environments. In this study, we explore the inherent capacity of variational autoencoders to disentangle the latent space of fundus images, with an aim to obtain a more robust and adaptable domain-invariant representation that effectively tackles the domain shift encountered in DR datasets. Despite the simplicity of our approach, we explore the efficacy of this classical method and demonstrate its ability to outperform contemporary state-of-the-art approaches for this task using publicly available datasets. Our findings challenge the prevailing assumption that highly sophisticated methods for DR classification are inherently superior for domain generalization. This highlights the importance of considering simple methods and adapting them to the challenging task of generalizing medical images, rather than solely relying on advanced techniques.

Flávio Coutinho, Luiz Chaimowicz

Iterating on creating pixel art character sprite sheets is essential to the game development process. However, it can take a lot of effort until the final versions containing different poses and animation clips are achieved. This paper investigates using conditional generative adversarial networks to aid the designers in creating such sprite sheets. We propose an architecture based on Pix2Pix to generate images of characters facing a target side (e.g., right) given sprites of them in a source pose (e.g., front). Experiments with small pixel art datasets yielded promising results, resulting in models with varying degrees of generalization, sometimes capable of generating images very close to the ground truth. We analyze the results through visual inspection and quantitatively with FID.

Rodrigo D. Moreira, Flávio Coutinho, Luiz Chaimowicz

Pixel art is a popular artistic style adopted in the gaming industry, and nowadays, it is often accompanied by modern rendering techniques. One example is dynamic lighting for the game sprites, for which normal mapping defines how the light interacts with the material represented by each pixel. Although there are different methods to generate normal maps for 3D games, applying them for pixel art may not yield correct results due to the style specificities. Therefore, this work compiles different normal map generation methods and study their applicability for pixel art, reducing the scarcity of existing material on the techniques and contributing to a qualitative analysis of the behavior of these methods in different case studies.

Hachem Dhouib, Stéphane Mathis, Lisa Bugnet et al.

Asteroseismology has revealed small core-to-surface rotation contrasts in stars in the whole HR diagram. This is the signature of strong transport of angular momentum (AM) in stellar interiors. One of the plausible candidates to efficiently carry AM is magnetic fields with various topologies that could be present in stellar radiative zones. Among them, strong axisymmetric azimuthal magnetic fields have received a lot of interest. Indeed, if they are subject to the so-called Tayler instability, the accompanying triggered Maxwell stresses can transport AM efficiently. In addition, the electromotive force induced by the fluctuations of magnetic and velocity fields could potentially sustain a dynamo action that leads to the regeneration of the initial strong axisymmetric azimuthal magnetic field. The key question we aim to answer is: can we detect signatures of these deep strong azimuthal magnetic fields? The only way to answer this question is asteroseismology and the best laboratories of study are intermediate-mass and massive stars. Most of these are rapid rotators during their main-sequence. Therefore, we have to study stellar pulsations propagating in stably stratified, rotating, and potentially strongly magnetised radiative zones. We generalise the traditional approximation of rotation by simultaneously taking general axisymmetric differential rotation and azimuthal magnetic fields into account in a non-perturbative way. Using this new formalism, we derive the asymptotic properties of magneto-gravito-inertial (MGI) waves and their period spacings. We find that toroidal magnetic fields induce a shift in the period spacings of MGI modes. An equatorial azimuthal magnetic field with an amplitude of the order of $10^5\,\rm G$ leads to signatures that can be detectable thanks to modern space photometry. More complex hemispheric configurations are more difficult to observe.

T. Nafde

It is a well-known fact, that music alone of all the arts and sciences has that dominating note of supreme mastership which compels unquestioned universal recognition. In painting, in sculpture, in architecture, in poetry, and in general literature in all its varying and varied moods and modes of expression, Indian music has won fame and occupied the highest place of appreciation in the world. It is admitted that Music is the last art to develop in any civilization, it must also be admitted that Indian civilization and culture have reached a point that would predicate a degree of development in Music, commensurate with our progress in other and kindred fields of creative activity.

Armèle Bellocher

I Nyoman Linggih

Statue is one form of fine arts which is known as the aesthetic experience which come out from the forms of three dimension. Ruci /Nawa Ruci is the form of God or Ida Shang Hyang Widhi in a form of one and only. The Ruci statue has an aesthetic appearance physically. The Ruci statue is a complete group, the united of one figure to another figure from point of view form structure and the existence of statue composition. The Ruci statue has functions: sacred function, ritual/ceremony function, religious aesthetic function. The Ruci statue is symbolize as a snake or dragon in the ocean wave which describe all commitment of human life in the real world which always bring the flows of human life uncertain. Bhima who is known as a micro cosmos figure or as a human being who looking for his true self and wants to find himself. Ruci/ Acintya represent in the statue is presented the sense of “Me” belong to every human life. So that the real phenomenon of Ruci statue is about dialog between soul (atma) with the highest soul (paramatma)in order to find out the real meaning.

Maeve O’Riordan

Hunting was an elite social pastime accessible to both men and women, of the correct social class, throughout the period 1860-1914. Female involvement in this sport preceded their widespread involvement in other sports and pastimes such as tennis and cycling. This article explores the contradictions inherent in women’s involvement in this masculine sport. The sport demanded that participants display contemporary masculine characteristics of bravery, strength, and independence, and yet it was open to both married and unmarried women of the gentry and ascendancy class in Ireland. The sport was a dangerous one, and considerable skill was demanded of all participants. However, daughters of hunting families were not persuaded against joining the hunt, and were instead encouraged to display the necessary skill and competitiveness to ride a horse side-saddle cross-country at speed; jumping stone walls and banks along the way. It was the norm for women to wear adapted dress modelled on masculine hunting attire, however this dress did not diminish their perceived femininity, and was perceived by some in hunting circles as the most alluring form of female dress. The article explores the numbers of women involved in the sport during the period utilising both contemporary fiction and directories. It also provides a case study of one woman’s experience as she partook of the hunt while also battling long term ill health; challenging the contemporary notion of women as inherently weak and unable for rigorous physical activity.