Visual Concepts Research Articles

Advancing Model Explainability: Visual Concept Knowledge Distillation for Concept Bottleneck Models

This study explores the integration of concept bottleneck models (CBMs) with knowledge distillation (KD) while preserving the locality characteristics of the CBM. Although KD proves effective in model compression, compressed models often lack interpretability in their decision-making process. We enhance comprehensive explainability by maintaining CBMs’ inherent interpretability through our novel approach to knowledge distillation. We introduce visual concept knowledge distillation (VICO-KD), which transfers both explicit and implicit visual concepts from the teacher to the student model while preserving the local interpretability of the CBM, enabling accurate classification and clear visualization of evidence. VICO-KD demonstrates superior performance on benchmark datasets compared to Vanilla-KD, ensuring the student model learns visual concepts while maintaining the local interpretation capabilities of the teacher CBM. Our methodology shows competitive performance against existing concept models, and the student model, trained via VICO-KD, exhibits enhanced performance compared to the teacher during interventions. This study highlights the effectiveness of combining a CBM with KD to improve both interpretability and explainability in compressed models while maintaining locality properties.

Human-centered perspectives and environmental impact: an ecocritical analysis of the Palace of Illusions

This paper explores anthropocentrism in Chitra Banerjee Divakaruni's The Palace of Illusions through the lens of ecocriticism, drawing on the theories of Lawrence Buell, Cheryll Glotfelty, Greg Garrard, Simon C. Estok, and Ursula K. Heise. Buell’s concept of the environmental imagination reveals how the novel reflects a human-centered view of nature, positioning the Pandavas' and Kaurava’s ambitions and conflicts as paramount, often disregarding the ecological consequences. Glotfelty’s foundational ecocriticism framework highlights how the novel's portrayal of nature as a mere backdrop to human drama underscores anthropocentric narratives, emphasizing human desires and struggles over ecological concerns. Garrard’s examination of anthropocentrism and biocentrism is crucial for understanding how the novel prioritizes human agency and perspective, contributing to environmental degradation. Estok’s insights into literature's historical and cultural contexts further contextualize how the novel's representation of nature reflects broader anthropocentric attitudes. Heise’s global environmental imagination framework helps situate the novel’s depiction of nature within a larger ecological context, illustrating the impact of human actions on the environment. This ecocritical analysis uncovers how The Palace of Illusions has remarkably presented lucidly and explicitly the human-centered worldview, revealing the implications of such perspectives on the natural world.

Imagination Is the Door to Amazement and Moral Imagination Holds the Key to Unlock It

The present article presents the concept of moral imagination in the general context of imagination as a journey of discovery and a reawakening of the values created through our feelings, emotions and other relevant life experiences that challenge us to appreciate the power of mind to transcend reality. In this vein, special attention should be paid to our moral principles that guide us through life, where we find moral imagination and its overwhelming capacity to engender new ideas, build new skills, and ultimately develop our critical thinking. Morality and imagination have many things in common, although morals refer to the realm of duties and obligations, whereas imagination concerns the faculty of the mind that deals with ideas from afar. To support this seemingly debatable concept, researchers, linguists, educators, and philosophers are brought into the discussion and they provide meaningful substance with theoretical and practical examples. That education should be the cultivation of goodness and good character is just one of the ensuing conclusions, compounded by the idea that practical knowledge also leads to moral imagination and its ancillary assets.

Visual Theory and Application of Interaction Design

This paper provides an overview of visual interaction design. It explores the theoretical foundations, key tools, practical applications, current limitations, and prospects. It explores the theoretical foundations, key tools, practical applications, current limitations, and prospects. First, the paper introduces visual interaction design's core concepts and principles. It explains how to use visual elements combined with user behavior to improve user experience. Then, it analyzes popular design tools like Figma, Photoshop, and p5.js, showing their roles in different design stages. Then, it analyzes popular design tools like Figma, Photoshop, and p5.js, showing their roles in different design stages. Next, the paper discusses successful applications of visual interaction design, such as augmented reality, adaptive interfaces, and personalized design, highlighting their impact on enhancing user experience. The paper also addresses limitations, including technical reliance, emotional interaction issues, accessibility challenges, and data privacy concerns. The paper also addresses limitations, including technical reliance, emotional interaction issues, accessibility challenges, and data privacy concerns. It aims to provide theoretical and practical guidance for designers and researchers, helping them understand and apply visual interaction design to enhance user experience.

Technological and Innovative Transformation in Marketing: Examination of Social Media Text Stream Visualization Concept with Bibliometric Analysis: Future Agenda

Changes in technology and innovation processes affect many areas. The impact of technology and innovative applications lead to radical changes in marketing strategies. Social media text stream visualization stands out as one of the most important tools of these changes. Social media text stream visualization allows the analysis of text data coming from social media platforms through graphics and infographics. In this way, social media text stream visualization allows the development of more effective and efficient strategies by combining technology and innovation in marketing. In this study, the Web of Science database is used to reveal in which areas the concept of social media text stream visualization has been used in the last 10 years through bibliometric analysis. After the inclusion and exclusion criteria are applied, the final sample consists of 12 refereed articles. Five separate analyses were conducted to test the sample. Performance analysis determined the publication years of the articles, their contributions by country, the outputs of relevant journals, and the sectors where this concept is used most intensively. The findings of the study provide a broad perspective on the research conducted to date and identify potential research gaps. Accordingly, it is seen that the studies within the scope of social media text stream visualization are mostly conducted in the fields of social media, advertising, ecommerce and market research. It was concluded that machine learning, big data, text analysis and time series methods were used in the studies. It is recommended that studies be conducted in the retail, tourism and accommodation and technology sectors for future research. This research aims to contribute to the field of marketing by revealing the gaps in the literature. The study also offers suggestions for future research to be conducted by academics and sectoral researchers.

Artificial fingerprints engraved through block-copolymers as nanoscale physical unclonable functions for authentication and identification

Besides causing financial losses and damage to the brand’s reputation, counterfeiting can threaten the health system and global security. In this context, physical unclonable functions (PUFs) have been proposed to overcome limitations of current anti-counterfeiting technologies. Here, we report on artificial fingerprints that can be directly engraved on a wide range of substrates through self-assembled block-copolymer templating as nanoscale PUFs for secure authentication and identification. Results show that morphological features can be exploited to encode fingerprint-like nanopatterns in binary code matrices representing a unique bit stream of information characterized by high uniqueness and entropy. A strategy based on computer vision concepts for authentication/identification in real-world scenarios is reported. Long-term reliable operation and robust authentication/identification against thermal treatment at cryogenic and high temperatures of the PUF have been demonstrated. These results pave the way for the realization of PUFs embracing the inherent stochasticity of self-assembled materials at the nanoscale.

Perancangan Desain Karakter Pada Buku Interaktif Satelit Bulan Untuk Anak Kelas 6 Sekolah Dasar

Learning about outer space, particularly satellites, is an important part of basic education that can foster motivation, curiosity, and interest in exploration among students. In the Semester Learning Plan (RPS) for Thematic Grade 6 Theme 8, the topic of the moon's satellite is often taught. However, this learning is often ineffective due to less creative teachers and inadequate learning media. Therefore, more engaging media is needed to increase student enthusiasm and understanding. This paper focuses on character design in the development of interactive book media about satellites for 6th-grade elementary school students. The method used is qualitative with qualitative descriptive analysis techniques. Primary data were obtained from interviews and observations, while secondary data were obtained from books and journals. The illustration design process includes determining the characteristics of each character, building character concepts, collecting references, determining design concepts, creating design alternatives, evaluating designs, and finalizing designs. Verbal and visual concepts are tailored to the target audience. The results of this design show that attractive interactive book media can enhance the understanding and interest of 6th-grade students in learning about outer space.

ANALISIS EFEKTIFITAS VISUALISASI PERMODELAN DESAIN ARSITEKTUR BERBASIS KECERDASAN BUATAN (AI)

This research focuses on the iteration of architectural modeling using artificial intelligence (AI) as a solution to generate visualization concepts in the architectural iteration process. It examines the development of AI in architecture and highlights AI's position in current architectural practice. AI has revolutionized the way architectural designs are developed, presented, and interpreted. With its ability to process complex data, AI accelerates the design process, enables the exploration of innovative solutions, and enhances understanding of projects before construction begins. AI is used in various applications, from automating visualizations to generating floor plans, opening new potentials in designing and visualizing architectural projects. However, the use of AI in architecture is still in its early stages, and challenges remain in applying AI to conceptual design stages. This research will analyze the effectiveness of AI in architectural modeling and design visualization, evaluating its impact on efficiency, creativity, and design output quality, and exploring limitations and future recommendations for AI use in architectural practice. Based on platform evaluations, MidJourney and DALL·E show superiority in visual quality and design accuracy, each with the highest scores. MidJourney and DALL·E are the top choices for creative and technical architectural visualization, while Leonardo AI and Bing AI show limitations in creativity and flexibility.

Environmental Visual Concept of Hybrid Animated Film ‘Si Dulang’ For Fine Dining Projection Mapping

Environmental Visual Concept of Hybrid Animated Film ‘Si Dulang’ For Fine Dining Projection Mapping

Формирование новых художественных приемов в оформлении спектаклей русской антрепризы на рубеже XIX-XX веков на примере театральных эскизов А. Бенуа, Л. Бакста, Н. Рериха и К. Коровина из фондов Государственного Русского музея

The purpose of the study is to identify the author’s artistic features and the processes of formation of new visual concepts in the design of performances of the Russian theatrical concern at the turn of the 19th-20th centuries in the set design works of A. Benois, L. Bakst, N. Roerich and K. Korovin, based on the analysis of rare sketches from the State Russian Museum. The article examines the key aesthetic and artistic trends that became decisive in the design of theatrical scenery during this period, as well as analyzes the influence of social, cultural and historical factors on the development of stage design. The issues such as the interaction of various art schools, the influence of European trends on Russian theatrical scenography and the development of stylistic trends in the design of performances are also considered. The research is based on the study of sketches that had not previously been shown to the general public and were not included in scientific publications, which characterizes them as a unique artistic material. The scientific novelty of the research lies in the systematization and analysis of sketches in a closed collection to identify innovative visual solutions in the context of socio-cultural changes and public attitudes of the specified period. The result of the study suggests the identification of individual artistic features in the theatrical work of each of the declared masters, which will allow us to talk about the Russian theater as a complex multifaceted system in which visual concepts are an integral part of an individual artistic solution.

Fashion, beauty and media

This introduction considers how the four research articles in this issue address the relation of fashion and/or beauty with media: specifically, the ‘older’ media of journalism and film, and ‘new’ media such as video blogs and TikTok. All of these venues have the capacity to communicate various visual and verbal concepts, with different relations to their audiences. The emergence of newer, digital platforms has disrupted the extent to which media can dictate visual codes and narratives, opening up fragmented and decentralized spaces where multiple, often conflicting, discourses of fashion and beauty coexist. These platforms also potentially articulate alternative beauty ideals and subcultural fashion trends that challenge the hegemonic standards of older media. At the same time, the responsibility of older media to foster ethical journalistic standards and social justice awareness to their audiences becomes intensified. The articles in this volume represent these potentialities for both older and newer media.

Structure-Guided Image Completion With Image-Level and Object-Level Semantic Discriminators.

Structure-guided image completion aims to inpaint a local region of an image according to an input guidance map from users. While such a task enables many practical applications for interactive editing, existing methods often struggle to hallucinate realistic object instances in complex natural scenes. Such a limitation is partially due to the lack of semantic-level constraints inside the hole region as well as the lack of a mechanism to enforce realistic object generation. In this work, we propose a learning paradigm that consists of semantic discriminators and object-level discriminators for improving the generation of complex semantics and objects. Specifically, the semantic discriminators leverage pretrained visual features to improve the realism of the generated visual concepts. Moreover, the object-level discriminators take aligned instances as inputs to enforce the realism of individual objects. Our proposed scheme significantly improves the generation quality and achieves state-of-the-art results on various tasks, including segmentation-guided completion, edge-guided manipulation and panoptically-guided manipulation on Places2 datasets. Furthermore, our trained model is flexible and can support multiple editing use cases, such as object insertion, replacement, removal and standard inpainting. In particular, our trained model combined with a novel automatic image completion pipeline achieves state-of-the-art results on the standard inpainting task.

Application of colour theory and visual merchandising principles in retail spaces

In retail settings, the strategic application of color theory and visual merchandising concepts is essential for influencing customer perception and increasing sales. One of the most obvious visual cues, color has a significant psychological impact on consumers, affecting their mood, perception, and buying habits. Retailers can create aesthetically pleasing spaces that suit their brand identity and client preferences by utilizing color theory concepts like complementary colours, warm versus cold tones, and color harmony. For instance, cool hues like blue and green express serenity and trust, while warm hues like red and yellow are frequently employed to convey a sense of urgency and enthusiasm. The creative placement of goods and displays to maximize consumer interaction and promote sales is known as visual merchandising. The utilization of contrasts, lighting, focal points, and product placement are important guidelines. Together with color theory, these components produce an engaging shopping experience that improves product visibility, makes navigating the store easier, and leads shoppers through it with ease. In addition to drawing in new clients, the strategic use of color psychology and visual merchandising strategies also affects their purchasing habits, increasing sales and building brand loyalty. Retail spaces may be transformed into dynamic, captivating settings that emotionally connect with customers through the use of this comprehensive strategy.

Adaptive CLIP for open-domain 3D model retrieval

In order to effectively enhance the practicality of 3D model retrieval, we adopt a single real image as the query sample for retrieving 3D models. However, the significant differences between 2D images and 3D models in terms of lighting conditions, textures and backgrounds, posing a great challenge for accurate retrieval. Existing work on 3D model retrieval mainly focuses on closed-domain research, while the open-domain condition where the category relationship between the query image and the 3D model is unknown is more in line with the needs of real scenarios. CLIP shows significant promise in comprehending open-world visual concepts, facilitating effective zero-shot image recognition. Based on this multimodal pre-training large language model, we introduce Adaptive Open-domain Semantic Nearest-neighbor Contrast (AOSNC), a method for learning and aligning multi-modal text, image, and 3D model. In order to solve the issue of inconsistent cross-domain categories and difficult sample correlation in open-domain, we construct a cross-modal bridge using CLIP. This model utilizes textual features to bridge the gap between 2D images and 3D model views. Additionally, we design an adaptive network layer to address the limitations of the pre-training model for 3D model views and enhance cross-modal alignment. We propose a mutual nearest-neighbor semantic alignment loss to address the challenge of aligning features from disparate modalities (text, images, and 3D models). This loss function enhances cross-modal learning by effectively associating and distinguishing features, improving retrieval accuracy. We conducted comprehensive experiments using the image-based 3D model retrieval dataset MI3DOR and the cross-domain 3D model retrieval dataset NTU-PSB to validate the superiority of the proposed method. Our results show significant improvements in several evaluation metrics, underscoring the efficacy of our method in augmenting cross-modal feature alignment and retrieval performance.

Imagination as an intellectual virtue

Abstract Many philosophers have recently defended the epistemic value of imagination. In this paper, we expand these discussions into the realm of virtue epistemology by proposing and defending a virtue-theoretic conception of imagination. On this account, the intellectual virtue of imagination is a character trait consisting of dispositions to engage skilfully in activities characteristic of imagining, with good judgement and from appropriate epistemic motivations. We argue that this approach helps to explain important connections between related, but distinct, intellectual virtues, including creativity and empathy, and reveals avenues for future work on how best to develop intellectually virtuous imagination.

Variation in the geometry of concept manifolds across human visual cortex.

Brain activity patterns in high-level visual cortex support accurate linear classification of visual concepts (e.g., objects or scenes). It has long been appreciated that the accuracy of linear classification in any brain area depends on the geometry of its concept manifolds-sets of brain activity patterns that encode images of a concept. However, it is unclear how the geometry of concept manifolds differs between regions of visual cortex that support accurate classification and those that don't, or how it differs between visual cortex and deep neural networks (DNNs). We estimated geometric properties of concept manifolds that, per a recent theory, directly determine the accuracy of simple "few-shot" linear classifiers. Using a large fMRI dataset, we show that variation in classification accuracy across human visual cortex is driven by a variation in a single geometric property: the distance between manifold centers ("geometric Signal"). In contrast, variation in classification accuracy across most DNN layers is driven by an increase in the effective number of manifold dimensions ("Dimensionality"). Despite this difference in the geometric properties that affect few-shot classification performance in the brain and DNNs, we find that Signal and Dimensionality are strongly, negatively correlated: when Signal increases across brain regions or DNN layers, Dimensionality decreases, and vice versa. We conclude that visual cortex and DNNs deploy different geometric strategies for accurate linear classification of concepts, even though both are subject to the same constraint.

Enhancing object recognition: The role of object knowledge decomposition and component-labeled datasets

Deep learning models’ decision-making processes can be elusive, often raising concerns about their reliability. To address this, we have introduced the Object Knowledge Decomposition and Components Label Dataset (OKD-CL), designed to improve the interpretability and accuracy of object recognition models. This dataset includes 99 categories from PartImageNet, each detailed with clear physical structures that align with human visual concepts. In a hierarchical structure, every category is described by Abstract Component Knowledge (ACK) descriptions and each image instance comes with Explicit Visual Knowledge (EVK) masks, highlighting the visual components’ appearance. By evaluating multiple deep neural networks guided with ACK and EVK (dual-knowledge-guidance approach), we saw better accuracy and a higher Foreground Reasoning Ratio (FRR), confirming our knowledge-guided method’s effectiveness. When used on the Hard-ImageNet dataset, this approach reduced the model’s reliance on incorrect feature assumptions without sacrificing classification accuracy. This hierarchical comprehension encouraged by OKD-CL is crucial in minimizing incorrect feature associations and strengthening model robustness. The entire code and dataset are available on: https://github.com/XiGuaBo/OKD-CL.

An Exploration of Design Strategies for Public-Oriented Scientific Visualization Communication

With the development of society, the public's attention and participation in science have been increasing, driving the evolution of scientific visualization representation forms. Scientific visualization has begun to have commodity attributes, and life science has become the key element and focus of scientific visualization creation. This study starts from the perspective of new media era communication design, and clarifies the concept and creative logic of scientific visualization through literature survey. The basic elements of creation are extracted. Through case analysis of the narrative methods and visual expression adopted in different scenarios of visualization design, the key points of scientific visualization creation from the perspective of communication design are summarized. Scientific visualization design has diversified development around different design orientations for target audiences in different scenarios. Scientists pay attention to the precision of visualization, while the public cares about the visual aesthetics and emotional response of visualization design. At this time, when communicators create for the public, they need to preconstruct an interesting story mode, adopt visual symbols familiar to the public, use modern media communication platforms, and such design models are more likely to be favored by the public

Letters to the Landscape (or an Alphabet in Ruins)

This article is a crossing through the Anthropocene. Between the body and the landscape, between the past and the future, between concepts and dances, between Edouard Glissant and the Atlantic Ocean, between tremor and uncertainty, between the Forest and Monoculture, between dance and the visual arts, between poetry and concepts, between the body and philosophy, between the animal and the plant, between what I desire and what I get, between Emanuele Coccia and the butterfly, between the thousand names of Gaia, the anthropology and what remains of our planet. They are letters thrown into the sea, directed to the landscapes that inhabit me, written with pieces of images and sounds that were inside my body/computer in these last years of journey. Shared in a list, like an alphabet in ruins, a (un)alphabetical order. Each letter carries a journey in itself: a way of doing and thinking about dance, an invention of a world that is possible to imagine today.

LRCN: Layer-residual Co-Attention Networks for visual question answering

Visual Question Answering (VQA) is a multimodal task requiring a collaborative understanding of fine-grained visual concepts and language semantics. The key to VQA research is constructing a framework for modeling inter and intramodal information interactions between intricate modalities. Due to the superior global view and the ability to capture the relationships within multimodal information, the Transformer and its variants have become the prime choice for VQA tasks. Despite this layer-by-layer architecture enabling answer reasoning by optimizing multimodal feature information, the information may still be lost when transferred from lower to higher layers. To solve such an issue, we propose a Layer-Residual Mechanism (LRM), a plug-and-play generic approach that can reduce the computation and memory overhead to almost negligible. By adding a residual straight-through line between adjacent layers that cascades the attention block in-depth, LRM mitigates the vanishing during information transfer, stabilizes training, and endeavors to overcome performance decline in VQA models at deeper layers. To verify the effectiveness and generality of the proposed LRM, we apply it to the Encoder–Decoder structure, the Pure-Stacking structure, and a specifically designed Co-Stacking structure that can simultaneously understand textual features and visual features called Layer-residual Co-Attention Networks (LRCN). Extensive ablation studies and comparative experiments on the benchmark VQA v2 and CLEVR datasets show that LRCN significantly outperforms the original architectures, demonstrating the superior effectiveness and compatibility of LRCN.