ACM Transactions on Graphics最新文献_第3页

AlignTex: Pixel-Precise Texture Generation from Multi-view Artwork AlignTex：从多视图图稿生成像素精确的纹理

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2025-07-27 DOI: 10.1145/3731158

Yuqing Zhang, Hao Xu, Yiqian Wu, Sirui Chen, Sirui Lin, Xiang Li, Xifeng Gao, Xiaogang Jin

{"title":"AlignTex: Pixel-Precise Texture Generation from Multi-view Artwork","authors":"Yuqing Zhang, Hao Xu, Yiqian Wu, Sirui Chen, Sirui Lin, Xiang Li, Xifeng Gao, Xiaogang Jin","doi":"10.1145/3731158","DOIUrl":"https://doi.org/10.1145/3731158","url":null,"abstract":"Current 3D asset creation pipelines typically consist of three stages: creating multi-view concept art, producing 3D meshes based on the artwork, and painting textures for the meshes—an often labor-intensive process. Automated texture generation offers significant acceleration, but prior methods, which fine-tune 2D diffusion models with multi-view input images, often fail to preserve pixel-level details. These methods primarily emphasize semantic and subject consistency, which do not meet the requirements of artwork-guided texture workflows. To address this, we present AlignTex , a novel framework for generating high-quality textures from 3D meshes and multi-view artwork, ensuring both appearance detail and geometric consistency. AlignTex operates in two stages: aligned image generation and texture refinement. The core of our approach, AlignNet , resolves complex misalignments by extracting information from both the artwork and the mesh, generating images compatible with orthographic projection while maintaining geometric and visual fidelity. After projecting aligned images into the texture space, further refinement addresses seams and self-occlusion using an inpainting model and a geometry-aware texture dilation method. Experimental results demonstrate that AlignTex outperforms baseline methods in generation quality and efficiency, offering a practical solution to enhance 3D asset creation in gaming and film production.","PeriodicalId":50913,"journal":{"name":"ACM Transactions on Graphics","volume":"26 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2025-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144712152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Order Matters: Learning Element Ordering for Graphic Design Generation 顺序问题：学习平面设计生成的元素顺序

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2025-07-27 DOI: 10.1145/3730858

Bo Yang, Ying Cao

{"title":"Order Matters: Learning Element Ordering for Graphic Design Generation","authors":"Bo Yang, Ying Cao","doi":"10.1145/3730858","DOIUrl":"https://doi.org/10.1145/3730858","url":null,"abstract":"The past few years have witnessed an emergent interest in building generative models for the graphic design domain. For adoption of powerful deep generative models with Transformer-based neural backbones, prior approaches formulate designs as ordered sequences of elements, and simply order the elements in a random or raster manner. We argue that such naive ordering methods are sub-optimal and there is room for improving sample quality through a better choice of order between graphic design elements. In this paper, we seek to explore the space of orderings to find the ordering strategy that optimizes the performance of graphic design generation models. For this, we propose a model, namely G enerative O rder L earner (GOL), which trains an autoregressive generator on design sequences, jointly with an ordering network that sort design elements to maximize the generation quality. With unsupervised training on vector graphic design data, our model is capable of learning a content-adaptive ordering approach, called neural order. Our experiments show that the generator trained with our neural order converges faster, achieving remarkably improved generation quality compared with using alternative ordering baselines. We conduct comprehensive analysis of our learned order to have a deeper understanding of its ordering behaviors. In addition, our learned order can generalize well to diffusion-based generative models and help design generators scale up excellently.","PeriodicalId":50913,"journal":{"name":"ACM Transactions on Graphics","volume":"12 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2025-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144712154","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Instant Self-Intersection Repair for 3D Meshes 即时自交叉修复3D网格

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2025-07-27 DOI: 10.1145/3731427

Wonjong Jang, Yucheol Jung, Gyeongmin Lee, Seungyong Lee

{"title":"Instant Self-Intersection Repair for 3D Meshes","authors":"Wonjong Jang, Yucheol Jung, Gyeongmin Lee, Seungyong Lee","doi":"10.1145/3731427","DOIUrl":"https://doi.org/10.1145/3731427","url":null,"abstract":"Self-intersection repair in static 3D surface meshes presents unique challenges due to the absence of temporal motion and penetration depth information—two critical elements typically leveraged in physics-based approaches. We introduce a novel framework that transforms local contact handling into a global repair strategy through a combination of local signed tangent-point energies and their gradient diffusion. At the heart of our method is a key insight: rather than computing expensive global repulsive potentials, we can effectively approximate long-range interactions by diffusing energy gradients from local contacts throughout the mesh surface. In turn, resolving complex self-intersections reduces to simply propagating local repulsive energies through standard diffusion mechanics and iteratively solving tractable local optimizations. We further accelerate convergence through our momentum-based optimizer, which adaptively regulates momentum based on gradient statistics to prevent overshooting while maintaining rapid intersection repair. The resulting algorithm handles a variety of challenging scenarios, from shallow contacts to deep penetrations, while providing computational efficiency suitable for interactive applications.","PeriodicalId":50913,"journal":{"name":"ACM Transactions on Graphics","volume":"130 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2025-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144712158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

HoLa: B-Rep Generation using a Holistic Latent Representation HoLa：使用整体潜在表示生成B-Rep

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2025-07-27 DOI: 10.1145/3730842

Yilin Liu, Duoteng Xu, Xingyao Yu, Xiang Xu, Daniel Cohen-Or, Hao Zhang, Hui Huang

{"title":"HoLa: B-Rep Generation using a Holistic Latent Representation","authors":"Yilin Liu, Duoteng Xu, Xingyao Yu, Xiang Xu, Daniel Cohen-Or, Hao Zhang, Hui Huang","doi":"10.1145/3730842","DOIUrl":"https://doi.org/10.1145/3730842","url":null,"abstract":"We introduce a novel representation for learning and generating Computer-Aided Design (CAD) models in the form of boundary representations (B-Reps). Our representation unifies the continuous geometric properties of B-Rep primitives in different orders (e.g., surfaces and curves) and their discrete topological relations in a holistic latent (HoLa) space. This is based on the simple observation that the topological connection between two surfaces is intrinsically tied to the geometry of their intersecting curve. Such a prior allows us to reformulate topology learning in B-Reps as a geometric reconstruction problem in Euclidean space. Specifically, we eliminate the presence of curves, vertices, and all the topological connections in the latent space by learning to distinguish and derive curve geometries from a pair of surface primitives via a neural intersection network. To this end, our holistic latent space is only defined on surfaces but encodes a full B-Rep model, including the geometry of surfaces, curves, vertices, and their topological relations. Our compact and holistic latent space facilitates the design of a first diffusion-based generator to take on a large variety of inputs including point clouds, single/multi-view images, 2D sketches, and text prompts. Our method significantly reduces ambiguities, redundancies, and incoherences among the generated B-Rep primitives, as well as training complexities inherent in prior multi-step B-Rep learning pipelines, while achieving greatly improved validity rate over current state of the art: 82% vs. ≈50%.","PeriodicalId":50913,"journal":{"name":"ACM Transactions on Graphics","volume":"57 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2025-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144712264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Clebsch Gauge Fluid on Particle Flow Maps 颗粒流图上的克莱施测量流体

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2025-07-27 DOI: 10.1145/3731194

Zhiqi Li, Candong Lin, Duowen Chen, Xinyi Zhou, Shiying Xiong, Bo Zhu

引用次数: 0

MaterialPicker: Multi-Modal DiT-Based Material Generation MaterialPicker：基于多模态dit的材料生成

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2025-07-27 DOI: 10.1145/3731199

Xiaohe Ma, Valentin Deschaintre, Miloš Hašan, Fujun Luan, Kun Zhou, Hongzhi Wu, Yiwei Hu

引用次数: 0

Topological Offsets 拓扑补偿

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2025-07-27 DOI: 10.1145/3731157

Daniel Zint, Zhouyuan Chen, Yifei Zhu, Denis Zorin, Teseo Schneider, Daniele Panozzo

引用次数: 0

TokenVerse: Versatile Multi-concept Personalization in Token Modulation Space TokenVerse：令牌调制空间中的多概念个性化

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2025-07-27 DOI: 10.1145/3730843

Daniel Garibi, Shahar Yadin, Roni Paiss, Omer Tov, Shiran Zada, Ariel Ephrat, Tomer Michaeli, Inbar Mosseri, Tali Dekel

{"title":"TokenVerse: Versatile Multi-concept Personalization in Token Modulation Space","authors":"Daniel Garibi, Shahar Yadin, Roni Paiss, Omer Tov, Shiran Zada, Ariel Ephrat, Tomer Michaeli, Inbar Mosseri, Tali Dekel","doi":"10.1145/3730843","DOIUrl":"https://doi.org/10.1145/3730843","url":null,"abstract":"We present TokenVerse - a method for multi-concept personalization, leveraging a pre-trained text-to-image diffusion model. Our framework can disentangle complex visual elements and attributes from as little as a single image, while enabling seamless plug-and-play generation of combinations of concepts extracted from multiple images. As opposed to existing works, TokenVerse can handle multiple images with multiple concepts each, and supports a wide-range of concepts, including objects, accessories, materials, pose, and lighting. Our work exploits a DiT-based text-to-image model, in which the input text affects the generation through both attention and modulation (shift and scale). We observe that the modulation space is semantic and enables localized control over complex concepts. Building on this insight, we devise an optimization-based framework that takes as input an image and a text description, and finds for each word a distinct direction in the modulation space. These directions can then be used to generate new images that combine the learned concepts in a desired configuration. We demonstrate the effectiveness of TokenVerse in challenging personalization settings, and showcase its advantages over existing methods.","PeriodicalId":50913,"journal":{"name":"ACM Transactions on Graphics","volume":"36 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2025-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144715620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

JGS2: Near Second-order Converging Jacobi/Gauss-Seidel for GPU Elastodynamics GPU弹性动力学的近二阶收敛Jacobi/Gauss-Seidel

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2025-07-27 DOI: 10.1145/3731183

Lei Lan, Zixuan Lu, Chun Yuan, Weiwei Xu, Hao Su, Huamin Wang, Chenfanfu Jiang, Yin Yang

{"title":"JGS2: Near Second-order Converging Jacobi/Gauss-Seidel for GPU Elastodynamics","authors":"Lei Lan, Zixuan Lu, Chun Yuan, Weiwei Xu, Hao Su, Huamin Wang, Chenfanfu Jiang, Yin Yang","doi":"10.1145/3731183","DOIUrl":"https://doi.org/10.1145/3731183","url":null,"abstract":"In parallel simulation, convergence and parallelism are often seen as inherently conflicting objectives. Improved parallelism typically entails lighter local computation and weaker coupling, which unavoidably slow the global convergence. This paper presents a novel GPU algorithm that achieves convergence rates comparable to fullspace Newton's method while maintaining good parallelizability just like the Jacobi method. Our approach is built on a key insight into the phenomenon of overshoot. Overshoot occurs when a local solver aggressively minimizes its local energy without accounting for the global context, resulting in a local update that undermines global convergence. To address this, we derive a theoretically second-order optimal solution to mitigate overshoot. Furthermore, we adapt this solution into a pre-computable form. Leveraging Cubature sampling, our runtime cost is only marginally higher than the Jacobi method, yet our algorithm converges nearly quadratically as Newton's method. We also introduce a novel full-coordinate formulation for more efficient pre-computation. Our method integrates seamlessly with the incremental potential contact method and achieves second-order convergence for both stiff and soft materials. Experimental results demonstrate that our approach delivers high-quality simulations and outperforms state-of-the-art GPU methods with 50× to 100× better convergence.","PeriodicalId":50913,"journal":{"name":"ACM Transactions on Graphics","volume":"63 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2025-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144715621","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Linear-Time Transport with Rectified Flows 带整流的线性时间输运

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2025-07-27 DOI: 10.1145/3731147

Khoa Do, David Coeurjolly, Pooran Memari, Nicolas Bonneel

{"title":"Linear-Time Transport with Rectified Flows","authors":"Khoa Do, David Coeurjolly, Pooran Memari, Nicolas Bonneel","doi":"10.1145/3731147","DOIUrl":"https://doi.org/10.1145/3731147","url":null,"abstract":"Matching probability distributions allows to compare or interpolate them, or model their manifold. Optimal transport is a tool that solves this matching problem. However, despite the development of numerous exact and approximate algorithms, these approaches remain too slow for large datasets due to the inherent challenge of optimizing transport plans. Taking intuitions from recent advances in rectified flows we propose an algorithm that, while not resulting in optimal transport plans, produces transport plans from uniform densities to densities stored on grids that resemble the optimal ones in practice. Our algorithm has linear-time complexity with respect to the problem size and is embarrassingly parallel. It is also trivial to implement, essentially computing three summed-area tables and advecting particles with velocities easily computed from these tables using simple arithmetic. This already allows for applications such as stippling and area-preserving mesh parameterization. Combined with linearized transport ideas, we further extend our approach to match two non-uniform distributions. This allows for wider applications such as shape interpolation or barycenters, matching the quality of more complex optimal or approximate transport solvers while resulting in orders of magnitude speedups. We illustrate our applications in 2D and 3D.","PeriodicalId":50913,"journal":{"name":"ACM Transactions on Graphics","volume":"27 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2025-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144712151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0