IEEE transactions on visualization and computer graphics最新文献

Parameterize Structure with Differentiable Template for 3D Shape Generation. 用可微模板参数化结构用于三维形状生成。

IEEE transactions on visualization and computer graphics Pub Date : 2025-06-27 DOI: 10.1109/TVCG.2025.3583987

Changfeng Ma, Pengxiao Guo, Shuangyu Yang, Yinuo Chen, Jie Guo, Chongjun Wang, Yanwen Guo, Wenping Wang

{"title":"Parameterize Structure with Differentiable Template for 3D Shape Generation.","authors":"Changfeng Ma, Pengxiao Guo, Shuangyu Yang, Yinuo Chen, Jie Guo, Chongjun Wang, Yanwen Guo, Wenping Wang","doi":"10.1109/TVCG.2025.3583987","DOIUrl":"https://doi.org/10.1109/TVCG.2025.3583987","url":null,"abstract":"Structural representation is crucial for reconstructing and generating editable 3D shapes with part semantics. Recent 3D shape generation works employ complicated networks and structure definitions relying on hierarchical annotations and pay less attention to the details inside parts. In this paper, we propose the method that parameterizes the shared structure in the same category using a differentiable template and corresponding fixed-length parameters. Specific parameters are fed into the template to calculate cuboids that indicate a concrete shape. We utilize the boundaries of three-view renderings of each cuboid to further describe the inside details. Shapes are represented with the parameters and three-view details inside cuboids, from which the SDF can be calculated to recover the object. Benefiting from our fixed-length parameters and three-view details, our networks for reconstruction and generation are simple and effective to learn the latent space. Our method can reconstruct or generate diverse shapes with complicated details, and interpolate them smoothly. Extensive evaluations demonstrate the superiority of our method on reconstruction from point cloud, generation, and interpolation.","PeriodicalId":94035,"journal":{"name":"IEEE transactions on visualization and computer graphics","volume":"PP ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144512861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Integrating User Input in Automated Object Placement for Augmented Reality. 在增强现实的自动对象放置中集成用户输入。

IEEE transactions on visualization and computer graphics Pub Date : 2025-06-27 DOI: 10.1109/TVCG.2025.3583745

Jalal Safari Bazargani, Abolghasem Sadeghi-Niaraki, Soo-Mi Choi

{"title":"Integrating User Input in Automated Object Placement for Augmented Reality.","authors":"Jalal Safari Bazargani, Abolghasem Sadeghi-Niaraki, Soo-Mi Choi","doi":"10.1109/TVCG.2025.3583745","DOIUrl":"https://doi.org/10.1109/TVCG.2025.3583745","url":null,"abstract":"Object placement in Augmented Reality (AR) is crucial for creating immersive and functional experiences. However, a critical research gap exists in combining user input with efficient automated placement, particularly in understanding spatial relationships and optimal placement. This study addresses this gap by presenting a novel object placement pipeline for AR applications that balances automation with user-directed placement. The pipeline employs entity recognition, object detection, depth estimation along with spawn area allocation to create a placement system. We compared our proposed method against manual placement in a comprehensive evaluation involving 50 participants. The evaluation included user experience questionnaires, a comparative study of task performance, and post-task interviews. Results indicate that our pipeline significantly reduces task completion time while maintaining comparable accuracy to manual placement. The UEQ-S and TENS scores revealed high user satisfaction. While manual placement offered more direct control, our method provided a more streamlined, efficient experience. This study contributes to the field of object placement in AR by demonstrating the potential of automated systems to enhance user experience and task efficiency.","PeriodicalId":94035,"journal":{"name":"IEEE transactions on visualization and computer graphics","volume":"PP ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144512860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Neural Implicit Representations for Multi-View Surface Reconstruction: A Survey. 基于神经隐式表征的多视图曲面重建研究进展。

IEEE transactions on visualization and computer graphics Pub Date : 2025-06-25 DOI: 10.1109/TVCG.2025.3582627

Xinyun Zhang, Ruiqi Yu, Shuang Ren

{"title":"Neural Implicit Representations for Multi-View Surface Reconstruction: A Survey.","authors":"Xinyun Zhang, Ruiqi Yu, Shuang Ren","doi":"10.1109/TVCG.2025.3582627","DOIUrl":"https://doi.org/10.1109/TVCG.2025.3582627","url":null,"abstract":"Diverging from conventional explicit geometric representations, neural implicit representations utilize continuous function approximators to encode 3D surfaces through parametric formulations including signed distance fields (SDF), unsigned distance fields (UDF), occupancy fields (OF), and neural radiance fields (NeRF). These approaches demonstrate superior multi-view reconstruction fidelity by inherently supporting non-manifold geometries and complex topological variations, establishing themselves as foundational tools in 3D reconstruction. Neural implicit representations can be applied to a diverse array of reconstruction tasks, including object-level reconstruction, scene-level reconstruction, open-surface reconstruction and dynamic reconstruction. The exponential advancement of neural implicit representations in 3D reconstruction necessitates systematic analysis of their evolving methodologies and applications. This survey presents a structured synthesis of cutting-edge research from 2020-2025, establishing a dual-axis taxonomy that categorizes techniques by geometric representation types and application scenarios. Through this survey, we aim to familiarize emerging researchers with the current landscape of neural implicit representation in surface reconstruction, assess innovative contributions and limitations in existing research, and encourage prospective research directions.","PeriodicalId":94035,"journal":{"name":"IEEE transactions on visualization and computer graphics","volume":"PP ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144499942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Revisit Point Cloud Quality Assessment: Current Advances and a Multiscale-Inspired Approach. 重访点云质量评估：当前进展和多尺度启发的方法。

IEEE transactions on visualization and computer graphics Pub Date : 2025-06-23 DOI: 10.1109/TVCG.2025.3582309

Junzhe Zhang, Tong Chen, Dandan Ding, Zhan Ma

{"title":"Revisit Point Cloud Quality Assessment: Current Advances and a Multiscale-Inspired Approach.","authors":"Junzhe Zhang, Tong Chen, Dandan Ding, Zhan Ma","doi":"10.1109/TVCG.2025.3582309","DOIUrl":"https://doi.org/10.1109/TVCG.2025.3582309","url":null,"abstract":"The demand for full-reference point cloud quality assessment (PCQA) has extended across various point cloud services. Unlike image quality assessment, where the reference and the distorted images are naturally aligned in coordinates and thus allow point-to-point (P2P) color assessment, the coordinates and attributes of a 3D point cloud may both suffer from distortion, making the P2P evaluation unsuitable. To address this, PCQA methods usually define a set of key points and construct a neighborhood around each key point for neighbor-to-neighbor (N2N) computation on geometry and attribute. However, state-of-the-art PCQA methods often exhibit limitations in certain scenarios due to insufficient consideration of key points and neighborhoods. To overcome these challenges, this paper proposes PQI, a simple yet efficient metric to index point cloud quality. PQI suggests using scale-wise key points to uniformly perceive distortions within a point cloud, along with a mild neighborhood size associated with each key point for compromised N2N computation. To achieve this, PQI employs a multiscale framework to obtain key points, ensuring comprehensive feature representation and distortion detection throughout the entire point cloud. Such a multiscale method merges every eight points into one in the downsampling processing, implicitly embedding neighborhood information into a single point and thereby eliminating the need for an explicitly large neighborhood. Further, within each neighborhood, simple features, such as geometry Euclidean distance difference and attribute value difference, are extracted. Feature similarity is then calculated between the reference and the distorted samples at each scale and linearly weighted to generate the final PQI score. Extensive experiments demonstrate the superiority of PQI, consistently achieving high performance across several widely recognized PCQA datasets. Moreover, PQI is highly appealing for practical applications due to its low complexity and flexible scale options.","PeriodicalId":94035,"journal":{"name":"IEEE transactions on visualization and computer graphics","volume":"PP ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144478335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Graphon-Based Visual Abstraction for Large Multi-Layer Networks. 基于图的大型多层网络视觉抽象。

IEEE transactions on visualization and computer graphics Pub Date : 2025-06-19 DOI: 10.1109/TVCG.2025.3581034

Ziliang Wu, Minfeng Zhu, Zhaosong Huang, Junxu Chen, Tiansheng Zhang, Shengbing Shi, Hao Li, Qiang Bai, Hongchao Qu, Xiuqi Huang, Wei Chen

{"title":"Graphon-Based Visual Abstraction for Large Multi-Layer Networks.","authors":"Ziliang Wu, Minfeng Zhu, Zhaosong Huang, Junxu Chen, Tiansheng Zhang, Shengbing Shi, Hao Li, Qiang Bai, Hongchao Qu, Xiuqi Huang, Wei Chen","doi":"10.1109/TVCG.2025.3581034","DOIUrl":"https://doi.org/10.1109/TVCG.2025.3581034","url":null,"abstract":"Graph visualization techniques provide a foundational framework for offering comprehensive overviews and insights into cloud computing systems, facilitating efficient management and ensuring their availability and reliability. Despite the enhanced computational and storage capabilities of larger-scale cloud computing architectures, they introduce significant challenges to traditional graph-based visualization due to issues of hierarchical heterogeneity, scalability, and data incompleteness. This paper proposes a novel abstraction approach to visualize large multi-layer networks. Our method leverages graphons, a probabilistic representation of network layers, to encompass three core steps: an inner-layer summary to identify stable and volatile substructures, an inter-layer mixup for aligning heterogeneous network layers, and a context-aware multi-layer joint sampling technique aimed at reducing network scale while retaining essential topological characteristics. By abstracting complex network data into manageable weighted graphs, with each graph depicting a distinct network layer, our approach renders these intricate systems accessible on standard computing hardware. We validate our methodology through case studies, quantitative experiments and expert evaluations, demonstrating its effectiveness in managing large multi-layer networks, as well as its applicability to broader network types such as transportation and social networks.","PeriodicalId":94035,"journal":{"name":"IEEE transactions on visualization and computer graphics","volume":"PP ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144334647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Cardboard Controller: A Cost-Effective Method to Support Complex Interactions in Mobile VR. 纸板控制器：在移动VR中支持复杂交互的一种经济有效的方法。

IEEE transactions on visualization and computer graphics Pub Date : 2025-06-19 DOI: 10.1109/TVCG.2025.3581158

Kristen Grinyer, Robert J Teather

引用次数: 0

Exploring Remote Collaborative Tasks: the Impact of Avatar Representation on Dyadic Haptic Interactions in Shared Virtual Environments. 探索远程协作任务：在共享虚拟环境中，虚拟化身表征对二元触觉交互的影响。

IEEE transactions on visualization and computer graphics Pub Date : 2025-06-17 DOI: 10.1109/TVCG.2025.3580546

Genki Sasaki, Hiroshi Igarashi

{"title":"Exploring Remote Collaborative Tasks: the Impact of Avatar Representation on Dyadic Haptic Interactions in Shared Virtual Environments.","authors":"Genki Sasaki, Hiroshi Igarashi","doi":"10.1109/TVCG.2025.3580546","DOIUrl":"https://doi.org/10.1109/TVCG.2025.3580546","url":null,"abstract":"This study is the first to explore the interplay between haptic interaction and avatar representation in Shared Virtual Environments (SVEs). Specifically, how these factors shape users' sense of social presence during dyadic collaborations, while assessing potential effects on task performance. In a series of experiments, participants performed the collaborative task with haptic interaction under four avatar representation conditions: avatars of both participant and partner were displayed, only the participant's avatar was displayed, only the partner's avatar was displayed, and no avatars were displayed. The study finds that avatar representation, especially of the partner, significantly enhances the perception of social presence, which haptic interaction alone does not fully achieve. However, neither the presence nor the type of avatar representation impacts the task performance or participants' force effort of the task, suggesting that haptic interaction provides sufficient interaction cues for the execution of the task. These results underscore the significance of integrating both visual and haptic modalities to optimize remote collaboration experiences in virtual environments, ensuring effective communication and a strong sense of social presence.","PeriodicalId":94035,"journal":{"name":"IEEE transactions on visualization and computer graphics","volume":"PP ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144319060","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

VOICE: Visual Oracle for Interaction, Conversation, and Explanation. 用于交互、对话和解释的可视化Oracle。

IEEE transactions on visualization and computer graphics Pub Date : 2025-06-16 DOI: 10.1109/TVCG.2025.3579956

Donggang Jia, Alexandra Irger, Lonni Besancon, Ondrej Strnad, Deng Luo, Johanna Bjorklund, Alexandre Kouyoumdjian, Anders Ynnerman, Ivan Viola

{"title":"VOICE: Visual Oracle for Interaction, Conversation, and Explanation.","authors":"Donggang Jia, Alexandra Irger, Lonni Besancon, Ondrej Strnad, Deng Luo, Johanna Bjorklund, Alexandre Kouyoumdjian, Anders Ynnerman, Ivan Viola","doi":"10.1109/TVCG.2025.3579956","DOIUrl":"https://doi.org/10.1109/TVCG.2025.3579956","url":null,"abstract":"We present VOICE, a novel approach to science communication that connects large language models' conversational capabilities with interactive exploratory visualization. VOICE introduces several innovative technical contributions that drive our conversational visualization framework. Based on the collected design requirements, we introduce a two-layer agent architecture that can perform task assignment, instruction extraction, and coherent content generation. We employ fine-tuning and prompt engineering techniques to tailor agents' performance to their specific roles and accurately respond to user queries. Our interactive text-to-visualization method generates a flythrough sequence matching the content explanation. In addition, natural language interaction provides capabilities to navigate and manipulate 3D models in real-time. The VOICE framework can receive arbitrary voice commands from the user and respond verbally, tightly coupled with a corresponding visual representation, with low latency and high accuracy. We demonstrate the effectiveness of our approach by implementing a proof-of-concept prototype and applying it to the molecular visualization domain: analyzing three 3D molecular models with multiscale and multi-instance attributes. Finally, we conduct a comprehensive evaluation of the system, including quantitative and qualitative analyses on our collected dataset, along with a detailed public user study and expert interviews. The results confirm that our framework and prototype effectively meet the design requirements and cater to the needs of diverse target users. All supplemental materials are available at https://osf.io/g7fbr.","PeriodicalId":94035,"journal":{"name":"IEEE transactions on visualization and computer graphics","volume":"PP ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144311112","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

$C^{2}D$: Context-aware Concept Decomposition for Personalized Text-to-image Synthesis. $C^{2}D$：面向个性化文本到图像合成的上下文感知概念分解。

IEEE transactions on visualization and computer graphics Pub Date : 2025-06-16 DOI: 10.1109/TVCG.2025.3579776

Jiang Xin, Xiaonan Fang, Xueling Zhu, Ju Ren, Yaoxue Zhang

{"title":"$C^{2}D$: Context-aware Concept Decomposition for Personalized Text-to-image Synthesis.","authors":"Jiang Xin, Xiaonan Fang, Xueling Zhu, Ju Ren, Yaoxue Zhang","doi":"10.1109/TVCG.2025.3579776","DOIUrl":"https://doi.org/10.1109/TVCG.2025.3579776","url":null,"abstract":"Concept decomposition is a technique for personalized text-to-image synthesis which learns textual embeddings of subconcepts from images that depicting an original concept. The learned subconcepts can then be composed to create new images. However, existing methods fail to address the issue of contextual conflicts when subconcepts from different sources are combined because contextual information remains encapsulated within the subconcept embeddings. To tackle this problem, we propose a Context-aware Concept Decomposition ($C^{2}D$) framework. Specifically, we introduce a Similarity-Guided Divergent Embedding (SGDE) method to obtain subconcept embeddings. Then, we eliminate the latent contextual dependence between the subconcept embeddings and reconstruct the contextual information using an independent contextual embedding. This independent context can be combined with various subconcepts, enabling more controllable text-to-image synthesis based on subconcept recombination. Extensive experimental results demonstrate that our method outperforms existing approaches in both image quality and contextual consistency.","PeriodicalId":94035,"journal":{"name":"IEEE transactions on visualization and computer graphics","volume":"PP ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144311111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Visualizationary: Automating Design Feedback for Visualization Designers Using LLMs. 可视化：使用llm的可视化设计师的自动化设计反馈。

IEEE transactions on visualization and computer graphics Pub Date : 2025-06-13 DOI: 10.1109/TVCG.2025.3579700

Sungbok Shin, Sanghyun Hong, Niklas Elmqvist

引用次数: 0