Hasil untuk "Art"

M. Ramdin, T. W. Loos, T. Vlugt

F. Zegers-Hochschild, G. Adamson, J. Mouzon et al.

N. Dubilier, C. Bergin, C. Lott

Jungwoo Lee, Meghan J. Cuddihy, N. Kotov

H. Vernon

F. B. Duijneveldt, J. G. C. M. D. D. Rijdt, J. -. Lenthe

W. Yeh

R. Arnheim

L. Simar, P. W. Wilson

Donald E. Knuth

R. Butler

C. Serhan, S. Brain, C. Buckley et al.

A recent focus meeting on Controlling Acute Inflammation was held in London, April 27–28, 2006, organized by D.W. Gilroy and S.D. Brain for the British Pharmacology Society. We concluded at the meeting that a consensus report was needed that addresses the rapid progress in this emerging field and details how the specific study of resolution of acute inflammation provides leads for novel anti‐inflammatory therapeutics, as well as defines the terms and key components of interest in the resolution process within tissues as appreciated today. The inflammatory response protects the body against infection and injury but can itself become dysregulated with deleterious consequences to the host. It is now evident that endogenous biochemical pathways activated during defense reactions can counter‐regulate inflammation and promote resolution. Hence, resolution is an active rather than a passive process, as once believed, which now promises novel approaches for the treatment of inflammation‐associated diseases based on endogenous agonists of resolution.—Serhan, C. N., Brain, S. D., Buckley, C. D., Gilroy, D. W., Haslett, C., O'Neill, L. A. J., Perretti, M., Rossi, A. G., Wallace, J. L. Resolution of inflammation: state of the art, definitions and terms. FASEB J. 21, 325–332 (2007)

P. Goovaerts

W. Richards

K. Hasan, Vincent Ng

While automatic keyphrase extraction has been examined extensively, state-of-theart performance on this task is still much lower than that on many core natural language processing tasks. We present a survey of the state of the art in automatic keyphrase extraction, examining the major sources of errors made by existing systems and discussing the challenges ahead.

Star A. Muir

Soumyaratna Debnath, Ashish Tiwari, Kaustubh Sadekar et al.

Recent advancements in learning-based methods have opened new avenues for exploring and interpreting art forms, such as shadow art, origami, and sketch art, through computational models. One notable visual art form is 3D Anamorphic Art in which an ensemble of arbitrarily shaped 3D objects creates a realistic and meaningful expression when observed from a particular viewpoint and loses its coherence over the other viewpoints. In this work, we build on insights from 3D Anamorphic Art to perform 3D object arrangement. We introduce RASP, a differentiable-rendering-based framework to arrange arbitrarily shaped 3D objects within a bounded volume via shadow (or silhouette)-guided optimization with an aim of minimal inter-object spacing and near-maximal occupancy. Furthermore, we propose a novel SDF-based formulation to handle inter-object intersection and container extrusion. We demonstrate that RASP can be extended to part assembly alongside object packing considering 3D objects to be "parts" of another 3D object. Finally, we present artistic illustrations of multi-view anamorphic art, achieving meaningful expressions from multiple viewpoints within a single ensemble.

Imke van Heerden

In early 2025, Augmented Intelligence - Christie's first AI art auction - drew criticism for showcasing a controversial genre. Amid wider legal uncertainty, artists voiced concerns over data mining practices, notably with respect to copyright. The backlash could be viewed as a microcosm of AI's contested position in the creative economy. Touching on the auction's presentation, reception, and results, this paper explores how, among social dissonance, machine learning finds its place in the artworld. Foregrounding responsible innovation, the paper provides a balanced perspective that champions creators' rights and brings nuance to this polarised debate. With a focus on exhibition design, it centres framing, which refers to the way a piece is presented to influence consumer perception. Context plays a central role in shaping our understanding of how good, valuable, and even ethical an artwork is. In this regard, Augmented Intelligence situates AI art within a surprisingly traditional framework, leveraging hallmarks of "high art" to establish the genre's cultural credibility. Generative AI has a clear economic dimension, converging questions of artistic merit with those of monetary worth. Scholarship on ways of seeing, or framing, could substantively inform the interpretation and evaluation of creative outputs, including assessments of their aesthetic and commercial value.

Nikoleta V. Nikolaidou, Anastasios Asvestas, Agathi Anthoula Kaminari et al.

Religious panel paintings (icons) play a pivotal role in the rituals of the Eastern Orthodox Christian Church. However, their continuous use often results in physical degradation, prompting remedial interventions. Quite commonly, alterations were treated by simply applying new paint layers directly over the decayed original, while in some cases, old icons were overpainted merely as a means to renovate and modernize them. Therefore, numerous overpainted icons are currently housed in churches, museums, and private collections across Greece. This study focuses on the investigation of a post-Byzantine icon of Christ Pantokrator, which displays extensive overpainting while retaining a few visible fragments of the original composition. The objective was to assess the extent and condition of preservation of the original artwork, to identify materials and techniques used both in the initial painting and in subsequent restoration phases, and to distinguish between those phases. To achieve these aims, a fully non-invasive diagnostic methodology was implemented, including visible light photography, ultraviolet radiation imaging (UVR/UVL), hyperspectral imaging (MuSIS HS), infrared reflectography (IRRef), X-ray radiography, and macroscopic X-ray fluorescence scanning (MA-XRF). The findings confirm that the original painting remains substantially preserved and is of high artistic quality. Moreover, analysis revealed at least two distinct phases of overpainting, likely dating from the 20th century, while the results suggest that the original artwork probably dates to the first half of the 18th century. The study highlights the need to use complementary techniques in order to non-invasively assess complex artifacts like overpainted icons and offers valuable insights into historical restoration practices providing foundation for future conservation planning.

Juniper Lovato, Julia Zimmerman, Isabelle Smith et al.

Generative AI tools are used to create art-like outputs and sometimes aid in the creative process. These tools have potential benefits for artists, but they also have the potential to harm the art workforce and infringe upon artistic and intellectual property rights. Without explicit consent from artists, Generative AI creators scrape artists' digital work to train Generative AI models and produce art-like outputs at scale. These outputs are now being used to compete with human artists in the marketplace as well as being used by some artists in their generative processes to create art. We surveyed 459 artists to investigate the tension between artists' opinions on Generative AI art's potential utility and harm. This study surveys artists' opinions on the utility and threat of Generative AI art models, fair practices in the disclosure of artistic works in AI art training models, ownership and rights of AI art derivatives, and fair compensation. Results show that a majority of artists believe creators should disclose what art is being used in AI training, that AI outputs should not belong to model creators, and express concerns about AI's impact on the art workforce and who profits from their art. We hope the results of this work will further meaningful collaboration and alignment between the art community and Generative AI researchers and developers.