Hasil untuk "Visual arts"

Oleksandr Pronkevich

The study focuses on a close reading of the Prologue, which was composed by Miguel Pérez, a Spanish Basilian monk and intellectual who taught at the University of Salamanca. In 1684, he published a book in Madrid which contained his translation of Yakiv Susha’s Life and Martyrdom of St. Josaphat Kuntsevych, which had been published in 1665 in Rome in the Latin language. This 1684 edition opened with the Prologue, also written by Pérez, an outstanding theological treatise which used the sophisticated stylistic devices of Baroque literature and rhetoric in order to demonstrate the spiritual authority of the Rules of St. Basil the Great. The result is amazing: in his Prologue, Pérez creates a myth concerning St. Josaphat, and skilfully inscribes it in the cultural space of the Spanish Golden Age. Together, the translation of Susha’s Life and Martyrdom of St. Josaphat Kuntsevych and Pérez’s commentaries have remained an unknown episode in the history of St. Josaphat’s veneration.

Zhangyong Tang, Tianyang Xu, Xuefeng Zhu et al.

The development of smart cities has led to the generation of massive amounts of multi-modal data in the context of a range of tasks that enable a comprehensive monitoring of the smart city infrastructure and services. This paper surveys one of the most critical tasks, multi-modal visual object tracking (MMVOT), from the perspective of multimodality analysis. Generally, MMVOT differs from single-modal tracking in four key aspects, data collection, modality alignment and annotation, model designing, and evaluation. Accordingly, we begin with an introduction to the relevant data modalities, laying the groundwork for their integration. This naturally leads to a discussion of challenges of multi-modal data collection, alignment, and annotation. Subsequently, existing MMVOT methods are categorised, based on different ways to deal with visible (RGB) and X modalities: programming the auxiliary X branch with replicated or non-replicated experimental configurations from the RGB branch. Here X can be thermal infrared (T), depth (D), event (E), near infrared (NIR), language (L), or sonar (S). The final part of the paper addresses evaluation and benchmarking. In summary, we undertake an omni survey of all aspects of multi-modal visual object tracking (VOT), covering six MMVOT tasks and featuring 338 references in total. In addition, we discuss the fundamental rhetorical question: Is multi-modal tracking always guaranteed to provide a superior solution to unimodal tracking with the help of information fusion, and if not, in what circumstances its application is beneficial. Furthermore, for the first time in this field, we analyse the distributions of the object categories in the existing MMVOT datasets, revealing their pronounced long-tail nature and a noticeable lack of animal categories when compared with RGB datasets.

Viktor von Wyl, Jürgen Bernard

Collaboration between health science and visual analytics research is often hindered by different, sometimes incompatible approaches to research design. Health science often follows hypothesis-driven protocols, registered in advance, and focuses on reproducibility and risk mitigation. Visual analytics, in contrast, relies on iterative data exploration, prioritizing insight generation and analytic refinement through user interaction. These differences create challenges in interdisciplinary projects, including misaligned terminology, unrealistic expectations about data readiness, divergent validation norms, or conflicting explainability requirements. To address these persistent tensions, we identify seven research needs and actions: (1) guidelines for broader community adoption, (2) agreement on quality and validation benchmarks, (3) frameworks for aligning research tasks, (4) integrated workflows combining confirmatory and exploratory stages, (5) tools for harmonizing terminology across disciplines, (6) dedicated bridging roles for transdisciplinary work, and (7) cultural adaptation and mutual recognition. We organize these needs in a framework with three areas: culture, standards, and processes. They can constitute a research agenda for developing reliable, reproducible, and clinically relevant data-centric methods.

Simone Arcagni

The concept of the Metaverse, originating from Neal Stephenson’s 1992 novel Snow Crash, has transitioned from a speculative fiction idea into a complex cultural and technological reality. This paper explores the evolution of the Metaverse as both a digital twin of the physical world and a new ‘cultural logic’ permeating various sectors such as gaming, education, and commerce. By integrating immersive technologies such as virtual reality, the Metaverse offers a blended “phygital” environment where users engage in activities ranging from social interactions to commercial transactions, seamlessly merging physical and digital realities. This study delves into how foremost technology leaders have influenced the Metaverse’s trajectory, focusing on transforming it from a gaming interface to a broad digital ecosystem. We analyze the role of blockchain technology in facilitating a network of interconnected spaces that allow for the preservation of digital identities and assets across platforms, highlighting the challenges and potential of achieving interoperability. Ultimately, this paper presents the Metaverse as a paradigm shift in digital interaction, suggesting future directions where digital and physical realities might further converge. Through a comprehensive review of technological advancements and cultural shifts, we discuss the implications of this convergence for future digital interaction frameworks and societal norms.

Runsen Xu, Zhiwei Huang, Tai Wang et al.

3D visual grounding is crucial for robots, requiring integration of natural language and 3D scene understanding. Traditional methods depending on supervised learning with 3D point clouds are limited by scarce datasets. Recently zero-shot methods leveraging LLMs have been proposed to address the data issue. While effective, these methods only use object-centric information, limiting their ability to handle complex queries. In this work, we present VLM-Grounder, a novel framework using vision-language models (VLMs) for zero-shot 3D visual grounding based solely on 2D images. VLM-Grounder dynamically stitches image sequences, employs a grounding and feedback scheme to find the target object, and uses a multi-view ensemble projection to accurately estimate 3D bounding boxes. Experiments on ScanRefer and Nr3D datasets show VLM-Grounder outperforms previous zero-shot methods, achieving 51.6% Acc@0.25 on ScanRefer and 48.0% Acc on Nr3D, without relying on 3D geometry or object priors. Codes are available at https://github.com/OpenRobotLab/VLM-Grounder .

Joey S. G. Mombarg, Conny Aerts, Geert Molenberghs

The theory the rotational and chemical evolution is incomplete, thereby limiting the accuracy of model-dependent stellar mass and age determinations. The $γ$ Doradus pulsators are excellent points of calibration for the current state-of-the-art stellar evolution models, as their gravity modes probe the physical conditions in the deep stellar interior. Yet, individual asteroseismic modelling of these stars is not always possible because of insufficient observed oscillation modes. This paper presents a novel method to derive distributions of the stellar mass, age, core-boundary mixing efficiency and initial rotation rates for $γ$ Dor stars. We compute a grid of rotating stellar evolution models covering the entire $γ$ Dor instability strip. We then use the observed distributions of the luminosity, effective temperature, buoyancy travel time and near-core rotation frequency of a sample of 539 stars to assign a statistical weight to each of our models. This weight is a measure of how likely the combination of a specific model is. We then compute weighted histograms to derive the most likely distributions of the fundamental stellar properties. We find that the rotation frequency at zero-age main sequence follows a normal distribution, peaking around 25% of the critical Keplerian rotation frequency. The probability-density function for extent of the core-boundary mixing zone, given by a factor $f_{\rm CBM}$ times the local pressure scale height (assuming an exponentially decaying parameterisation) decreases linearly with increasing $f_{\rm CBM}$. Converting the distribution of fractions of critical rotation at the zero-age main sequence to units of d$^{-1}$, we find most F-type stars start the main sequence with a rotation frequency between 0.5 and 2 d$^{-1}$. Regarding the core-boundary mixing efficiency, we find that it is generally weak in this mass regime.

Chase Stokes, Marti A. Hearst

Visualization research tends to de-emphasize consideration of the textual context in which its images are placed. We argue that visualization research should consider textual representations as a primary alternative to visual options when assessing designs, and when assessing designs, equal attention should be given to the construction of the language as to the visualizations. We also call for a consideration of readability when integrating visualizations with written text. In highlighting these points, visualization research would be elevated in efficacy and demonstrate thorough accounting for viewers' needs and responses.

Görkay Aydemir, Weidi Xie, Fatma Güney

Large-scale vision foundation models have demonstrated remarkable success across various tasks, underscoring their robust generalization capabilities. While their proficiency in two-view correspondence has been explored, their effectiveness in long-term correspondence within complex environments remains unexplored. To address this, we evaluate the geometric awareness of visual foundation models in the context of point tracking: (i) in zero-shot settings, without any training; (ii) by probing with low-capacity layers; (iii) by fine-tuning with Low Rank Adaptation (LoRA). Our findings indicate that features from Stable Diffusion and DINOv2 exhibit superior geometric correspondence abilities in zero-shot settings. Furthermore, DINOv2 achieves performance comparable to supervised models in adaptation settings, demonstrating its potential as a strong initialization for correspondence learning.

Qureshi Saadi Ahmed saeid

It is known that visual art is the art that is capable of making the spectator turns from state to another. Cinema is considered one of the most powerful and effective visual arts, and it has the ability to influence and persuade.In the beginning, in the field of visual effects cinema depended on traditional and simple methods that commensurate with the culture of the spectator at this time, then the technical progress was clearly and rapidly followed in the technological fields that helped to apply all kinds of optical illusions, which greatly contributed to change the shape and content of the movie."The art of Makeup” is considered one of the most important branches of optical illusions.Where it comes to mind that the art of makeup is only related to beautifying artists and hiding facial flaws to show them brilliantly, but the truth is that the art of makeup is the art of changing the appearance of the real face of the actor in a way that suits the character he performs, by using powders, colors….etc., to create certain facial features required to express the character or to be reincarnated.In addition to its application by many people to attend various artistic and masquerade events, and we often notice many people are using it in daily life, and they are often teenagers.Also cinematic makeup can deliver any kind of information to viewers without using words or wasting time, make-up in dramas differs from ordinary make-up, as it is subject to study as a self-stand art, because make-up has to be compatible with bright lighting, decorative angles and accessories.This type of art has become a pillar that specialized institutes are opened based on it, where young talents who found inspiration in cinematic works and other arts to paint them on faces and bodies using various colors and accessories could be contained, so that this type of art opens doors in front of their imagination to be creative and show their ideas no matter how strange and crazy it seems.

Laura Mason

This article follows the lead of Richard Dyer and Devon Carbado in naming whiteness as a racial identity and uses intersectional analysis to explore Jacques Audiard’s depiction of race and gender in Dheepan and The Sisters Brothers. Both movies depart from the gender norms of earlier Audiard films by doing away with female saviors, so making male protagonists responsible for controlling their own violence. Both films also reflect Audiard’s determination to foreground Black and Brown characters in ways that better reflect the racial and cultural heterogeneity of France and the world. And yet, unorthodox casting choices and visual framing distance these same characters of color from responsibility for violence. Such an approach might be interpreted as a challenge to film makers’ historical tendency to cast Black and Brown men as especially violent. However, Audiard’s films commonly elicit sympathy for white men who exercise violence. Accordingly, Audiard’s denial of authority for violence to Black and Brown characters intimates than they can only be sympathetic if seen to be more upright than his white protagonists.

Alejandro García García

Edmund Berger. Madrid, Enclave de libros. 390 páginas. ISBN:978-84-125590-0-2.

Marina Evers, Raphael Wittkowski, Lars Linsen

Simulation ensembles are a common tool in physics for understanding how a model outcome depends on input parameters. We analyze an active particle system, where each particle can use energy from its surroundings to propel itself. A multi-dimensional feature vector containing all particles' motion information can describe the whole system at each time step. The system's behavior strongly depends on input parameters like the propulsion mechanism of the particles. To understand how the time-varying behavior depends on the input parameters, it is necessary to introduce new measures to quantify the difference of the dynamics of the ensemble members. We propose a tool that supports the interactive visual analysis of time-varying feature-vector ensembles. A core component of our tool allows for the interactive definition and refinement of new measures that can then be used to understand the system's behavior and compare the ensemble members. Different visualizations support the user in finding a characteristic measure for the system. By visualizing the user-defined measure, the user can then investigate the parameter dependencies and gain insights into the relationship between input parameters and simulation output.

Andres Karjus, Mar Canet Solà, Tillmann Ohm et al.

The quantification of visual aesthetics and complexity have a long history, the latter previously operationalized via the application of compression algorithms. Here we generalize and extend the compression approach beyond simple complexity measures to quantify algorithmic distance in historical and contemporary visual media. The proposed "ensemble" approach works by compressing a large number of transformed versions of a given input image, resulting in a vector of associated compression ratios. This approach is more efficient than other compression-based algorithmic distances, and is particularly suited for the quantitative analysis of visual artifacts, because human creative processes can be understood as algorithms in the broadest sense. Unlike comparable image embedding methods using machine learning, our approach is fully explainable through the transformations. We demonstrate that the method is cognitively plausible and fit for purpose by evaluating it against human complexity judgments, and on automated detection tasks of authorship and style. We show how the approach can be used to reveal and quantify trends in art historical data, both on the scale of centuries and in rapidly evolving contemporary NFT art markets. We further quantify temporal resemblance to disambiguate artists outside the documented mainstream from those who are deeply embedded in Zeitgeist. Finally, we note that compression ensembles constitute a quantitative representation of the concept of visual family resemblance, as distinct sets of dimensions correspond to shared visual characteristics otherwise hard to pin down. Our approach provides a new perspective for the study of visual art, algorithmic image analysis, and quantitative aesthetics more generally.

Ryuji Watanabe, Hideaki Ishibashi, Tetsuo Furukawa

Visual analytics (VA) is a visually assisted exploratory analysis approach in which knowledge discovery is executed interactively between the user and system in a human-centered manner. The purpose of this study is to develop a method for the VA of set data aimed at supporting knowledge discovery and member selection. A typical target application is a visual support system for team analysis and member selection, by which users can analyze past teams and examine candidate lineups for new teams. Because there are several difficulties, such as the combinatorial explosion problem, developing a VA system of set data is challenging. In this study, we first define the requirements that the target system should satisfy and clarify the accompanying challenges. Then we propose a method for the VA of set data, which satisfies the requirements. The key idea is to model the generation process of sets and their outputs using a manifold network model. The proposed method visualizes the relevant factors as a set of topographic maps on which various information is visualized. Furthermore, using the topographic maps as a bidirectional interface, users can indicate their targets of interest in the system on these maps. We demonstrate the proposed method by applying it to basketball teams, and compare with a benchmark system for outcome prediction and lineup reconstruction tasks. Because the method can be adapted to individual application cases by extending the network structure, it can be a general method by which practical systems can be built.

Huangying Zhan, Chamara Saroj Weerasekera, Jia-Wang Bian et al.

Multi-view geometry-based methods dominate the last few decades in monocular Visual Odometry for their superior performance, while they have been vulnerable to dynamic and low-texture scenes. More importantly, monocular methods suffer from scale-drift issue, i.e., errors accumulate over time. Recent studies show that deep neural networks can learn scene depths and relative camera in a self-supervised manner without acquiring ground truth labels. More surprisingly, they show that the well-trained networks enable scale-consistent predictions over long videos, while the accuracy is still inferior to traditional methods because of ignoring geometric information. Building on top of recent progress in computer vision, we design a simple yet robust VO system by integrating multi-view geometry and deep learning on Depth and optical Flow, namely DF-VO. In this work, a) we propose a method to carefully sample high-quality correspondences from deep flows and recover accurate camera poses with a geometric module; b) we address the scale-drift issue by aligning geometrically triangulated depths to the scale-consistent deep depths, where the dynamic scenes are taken into account. Comprehensive ablation studies show the effectiveness of the proposed method, and extensive evaluation results show the state-of-the-art performance of our system, e.g., Ours (1.652%) v.s. ORB-SLAM (3.247%}) in terms of translation error in KITTI Odometry benchmark. Source code is publicly available at: \href{https://github.com/Huangying-Zhan/DF-VO}{DF-VO}.

Françoise Le Corre, Valérie Morisson

Aurel Rotival

This article suggests to study an aesthetic pattern shared by three European movies, directed between the ‘60s and the ‘70s. The Hawks and the Sparrows (P. P. Pasolini, 1966), Long Live Death (F. Arrabal, 1971), and Red Psalm (M. Jancsó, 1972), are all three characterized by a sequence that replay politically the religious scheme of communion, directly borrowed from the Christian sacrament of the Eucharist. It is about seeing in this figurative community the index of a singularly apocalyptic moment experienced by the Western world. Following this catastrophic diagnosis, it is with the religious notion of salvation that a certain section of European Marxism had to think the political concepts of revolution and emancipation. This should lead some communist artists and thinkers to reconsider afresh the memorial, communal and salvific virtues originally transported by religious representations and ceremonies – a turning point, both anthropological and religious, whose communist communions spotted in these three films bear the mark. These three examples are also an opportunity to pay attention to the contextual conditions which, in European cinema, can encourage the emergence of common themes and patterns transcending generic, stylistic or regional differences.

Cheng-Che Lee, Wan-Yi Lin, Yen-Ting Shih et al.

Music-to-visual style transfer is a challenging yet important cross-modal learning problem in the practice of creativity. Its major difference from the traditional image style transfer problem is that the style information is provided by music rather than images. Assuming that musical features can be properly mapped to visual contents through semantic links between the two domains, we solve the music-to-visual style transfer problem in two steps: music visualization and style transfer. The music visualization network utilizes an encoder-generator architecture with a conditional generative adversarial network to generate image-based music representations from music data. This network is integrated with an image style transfer method to accomplish the style transfer process. Experiments are conducted on WikiArt-IMSLP, a newly compiled dataset including Western music recordings and paintings listed by decades. By utilizing such a label to learn the semantic connection between paintings and music, we demonstrate that the proposed framework can generate diverse image style representations from a music piece, and these representations can unveil certain art forms of the same era. Subjective testing results also emphasize the role of the era label in improving the perceptual quality on the compatibility between music and visual content.

Maria Francesca Piredda

Recently a series of films made by immigrants to Italy have emerged. These nevertheless remain marginal to the national industry, in part as Italy has no centralized policies that support the development of a “new Italian cinema” legally. This affects the production/distribution strategies and representational modes of migration cinema. This essay focuses on MigrArti, a call opened by MiBAC in 2015, which promotes creative initiatives in the fields of cinema, music, theatre and art, enabling migrants to introduce their traditions and their values in Italian society and culture. The objective is threefold: to question the concept of "Italian cinema" in relation to cultural shifts; to provide a picture of the funding of migrant cinema in Italy; to analyse the structure of the MigrArti call, in order to understand which subjects, production/distribution models and themes gain support, and why.

Christopher Nagle

This article reviews the world premiere of Kate Hamill's Mansfield Park directed by Stuart Carden and produced for the Northlight Theatre in Chicago in November and December 2018. Hamill’s bold new adaptation is notable for foregrounding the contexts of empire and the slave trade undergirding the novel, and in ultimately offering a feminist fairy-tale of radical self-assertion and self-determination for its heroine.