ACM Transactions on Graphics最新文献

PhysFiT: Physical-aware 3D Shape Understanding for Finishing Incomplete Assembly PhysFiT：物理感知三维形状理解，用于完成不完整装配

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2024-10-29 DOI: 10.1145/3702226

Weihao Wang, Mingyu You, Hongjun Zhou, Bin He

{"title":"PhysFiT: Physical-aware 3D Shape Understanding for Finishing Incomplete Assembly","authors":"Weihao Wang, Mingyu You, Hongjun Zhou, Bin He","doi":"10.1145/3702226","DOIUrl":"https://doi.org/10.1145/3702226","url":null,"abstract":"Understanding the part composition and structure of 3D shapes is crucial for a wide range of 3D applications, including 3D part assembly and 3D assembly completion. Compared to 3D part assembly, 3D assembly completion is more complicated which involves repairing broken or incomplete furniture that miss several parts with a toolkit. The primary challenge persists in how to reveal the potential part relations to infer the absent parts from multiple indistinguishable candidates with similar geometries, and complete for well-connected, structurally stable and aesthetically pleasing assemblies. This task necessitates not only specialized knowledge of part composition but, more importantly, an awareness of physical constraints, i.e. , connectivity, stability, and symmetry. Neglecting these constraints often results in assemblies that, although visually plausible, are impractical. To address this challenge, we propose PhysFiT, a physical-aware 3D shape understanding framework. This framework is built upon attention-based part relation modeling and incorporates connection modeling, simulation-free stability optimization and symmetric transformation consistency. We evaluate its efficacy on 3D part assembly and 3D assembly completion, a novel assembly task presented in this work. Extensive experiments demonstrate the effectiveness of PhysFiT in constructing geometrically sound and physically compliant assemblies.","PeriodicalId":50913,"journal":{"name":"ACM Transactions on Graphics","volume":null,"pages":null},"PeriodicalIF":6.2,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142541706","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

Synchronized tracing of primitive-based implicit volumes 基于基元的隐式卷的同步追踪

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2024-10-28 DOI: 10.1145/3702227

Cédric Zanni

引用次数: 0

TriHuman : A Real-time and Controllable Tri-plane Representation for Detailed Human Geometry and Appearance Synthesis TriHuman：用于详细人体几何和外观合成的实时可控三平面表示法

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2024-09-24 DOI: 10.1145/3697140

Heming Zhu, Fangneng Zhan, Christian Theobalt, Marc Habermann

{"title":"TriHuman : A Real-time and Controllable Tri-plane Representation for Detailed Human Geometry and Appearance Synthesis","authors":"Heming Zhu, Fangneng Zhan, Christian Theobalt, Marc Habermann","doi":"10.1145/3697140","DOIUrl":"https://doi.org/10.1145/3697140","url":null,"abstract":"Creating controllable, photorealistic, and geometrically detailed digital doubles of real humans solely from video data is a key challenge in Computer Graphics and Vision, especially when real-time performance is required. Recent methods attach a neural radiance field (NeRF) to an articulated structure, e.g., a body model or a skeleton, to map points into a pose canonical space while conditioning the NeRF on the skeletal pose. These approaches typically parameterize the neural field with a multi-layer perceptron (MLP) leading to a slow runtime. To address this drawback, we propose TriHuman a novel human-tailored, deformable, and efficient tri-plane representation, which achieves real-time performance, state-of-the-art pose-controllable geometry synthesis as well as photorealistic rendering quality. At the core, we non-rigidly warp global ray samples into our undeformed tri-plane texture space, which effectively addresses the problem of global points being mapped to the same tri-plane locations. We then show how such a tri-plane feature representation can be conditioned on the skeletal motion to account for dynamic appearance and geometry changes. Our results demonstrate a clear step towards higher quality in terms of geometry and appearance modeling of humans as well as runtime performance.","PeriodicalId":50913,"journal":{"name":"ACM Transactions on Graphics","volume":null,"pages":null},"PeriodicalIF":6.2,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142374643","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

DAMO: A Deep Solver for Arbitrary Marker Configuration in Optical Motion Capture DAMO：光学运动捕捉中任意标记配置的深度求解器

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2024-09-14 DOI: 10.1145/3695865

KyeongMin Kim, SeungWon Seo, DongHeun Han, HyeongYeop Kang

{"title":"DAMO: A Deep Solver for Arbitrary Marker Configuration in Optical Motion Capture","authors":"KyeongMin Kim, SeungWon Seo, DongHeun Han, HyeongYeop Kang","doi":"10.1145/3695865","DOIUrl":"https://doi.org/10.1145/3695865","url":null,"abstract":"Marker-based optical motion capture (mocap) systems are increasingly utilized for acquiring 3D human motion, offering advantages in capturing the subtle nuances of human movement, style consistency, and ease of obtaining desired motion. Motion data acquisition via mocap typically requires laborious marker labeling and motion reconstruction, recent deep-learning solutions have aimed to automate the process. However, such solutions generally presuppose a fixed marker configuration to reduce learning complexity, thereby limiting flexibility. To overcome the limitation, we introduce DAMO, an end-to-end deep solver, proficiently inferring arbitrary marker configurations and optimizing pose reconstruction. DAMO outperforms state-of-the-art like SOMA and MoCap-Solver in scenarios with significant noise and unknown marker configurations. We expect that DAMO will meet various practical demands such as facilitating dynamic marker configuration adjustments during capture sessions, processing marker clouds irrespective of whether they employ mixed or entirely unknown marker configurations, and allowing custom marker configurations to suit distinct capture scenarios. DAMO code and pretrained models are available at https://github.com/CritBear/damo .","PeriodicalId":50913,"journal":{"name":"ACM Transactions on Graphics","volume":null,"pages":null},"PeriodicalIF":6.2,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142374676","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

RNA: Relightable Neural Assets RNA：可重燃的神经资产

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2024-09-13 DOI: 10.1145/3695866

Krishna Mullia, Fujun Luan, Xin Sun, Miloš Hašan

{"title":"RNA: Relightable Neural Assets","authors":"Krishna Mullia, Fujun Luan, Xin Sun, Miloš Hašan","doi":"10.1145/3695866","DOIUrl":"https://doi.org/10.1145/3695866","url":null,"abstract":"High-fidelity 3D assets with materials composed of fibers (including hair), complex layered material shaders, or fine scattering geometry are critical in high-end realistic rendering applications. Rendering such models is computationally expensive due to heavy shaders and long scattering paths. Moreover, implementing the shading and scattering models is non-trivial and has to be done not only in the 3D content authoring software (which is necessarily complex), but also in all downstream rendering solutions. For example, web and mobile viewers for complex 3D assets are desirable, but frequently cannot support the full shading complexity allowed by the authoring application. Our goal is to design a neural representation for 3D assets with complex shading that supports full relightability and full integration into existing renderers. We provide an end-to-end shading solution at the first intersection of a ray with the underlying geometry. All shading and scattering is precomputed and included in the neural asset; no multiple scattering paths need to be traced, and no complex shading models need to be implemented to render our assets, beyond a single neural architecture. We combine an MLP decoder with a feature grid. Shading consists of querying a feature vector, followed by an MLP evaluation producing the final reflectance value. Our method provides high-fidelity shading, close to the ground-truth Monte Carlo estimate even at close-up views. We believe our neural assets could be used in practical renderers, providing significant speed-ups and simplifying renderer implementations.","PeriodicalId":50913,"journal":{"name":"ACM Transactions on Graphics","volume":null,"pages":null},"PeriodicalIF":6.2,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142374644","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

Speed-Aware Audio-Driven Speech Animation using Adaptive Windows 使用自适应窗口的速度感知音频驱动语音动画

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2024-08-31 DOI: 10.1145/3691341

Sunjin Jung, Yeongho Seol, Kwanggyoon Seo, Hyeonho Na, Seonghyeon Kim, Vanessa Tan, Junyong Noh

{"title":"Speed-Aware Audio-Driven Speech Animation using Adaptive Windows","authors":"Sunjin Jung, Yeongho Seol, Kwanggyoon Seo, Hyeonho Na, Seonghyeon Kim, Vanessa Tan, Junyong Noh","doi":"10.1145/3691341","DOIUrl":"https://doi.org/10.1145/3691341","url":null,"abstract":"We present a novel method that can generate realistic speech animations of a 3D face from audio using multiple adaptive windows. In contrast to previous studies that use a fixed size audio window, our method accepts an adaptive audio window as input, reflecting the audio speaking rate to use consistent phonemic information. Our system consists of three parts. First, the speaking rate is estimated from the input audio using a neural network trained in a self-supervised manner. Second, the appropriate window size that encloses the audio features is predicted adaptively based on the estimated speaking rate. Another key element lies in the use of multiple audio windows of different sizes as input to the animation generator: a small window to concentrate on detailed information and a large window to consider broad phonemic information near the center frame. Finally, the speech animation is generated from the multiple adaptive audio windows. Our method can generate realistic speech animations from in-the-wild audios at any speaking rate, i.e., fast raps, slow songs, as well as normal speech. We demonstrate via extensive quantitative and qualitative evaluations including a user study that our method outperforms state-of-the-art approaches.","PeriodicalId":50913,"journal":{"name":"ACM Transactions on Graphics","volume":null,"pages":null},"PeriodicalIF":6.2,"publicationDate":"2024-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142374647","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

ControlMat: A Controlled Generative Approach to Material Capture 控制垫：材料捕捉的受控生成方法

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2024-08-27 DOI: 10.1145/3688830

Giuseppe Vecchio, Rosalie Martin, Arthur Roullier, Adrien Kaiser, Romain Rouffet, Valentin Deschaintre, Tamy Boubekeur

引用次数: 0

Resolving Collisions in Dense 3D Crowd Animations 解决密集 3D 人群动画中的碰撞问题

IF 7.8 1区计算机科学

ACM Transactions on Graphics Pub Date : 2024-08-10 DOI: 10.1145/3687266

Gonzalo Gomez-Nogales, Melania Prieto-Martin, Cristian Romero, Marc Comino-Trinidad, Pablo Ramon-Prieto, A. Olivier, Ludovic Hoyet, Miguel Otaduy, J. Pettré, Dan Casas

{"title":"Resolving Collisions in Dense 3D Crowd Animations","authors":"Gonzalo Gomez-Nogales, Melania Prieto-Martin, Cristian Romero, Marc Comino-Trinidad, Pablo Ramon-Prieto, A. Olivier, Ludovic Hoyet, Miguel Otaduy, J. Pettré, Dan Casas","doi":"10.1145/3687266","DOIUrl":"https://doi.org/10.1145/3687266","url":null,"abstract":"We propose a novel contact-aware method to synthesize highly-dense 3D crowds of animated characters. Existing methods animate crowds by, first, computing the 2D global motion approximating subjects as 2D particles and, then, introducing individual character motions without considering their surroundings. This creates the illusion of a 3D crowd, but, with density, characters frequently intersect each other since character-to-character contact is not modeled. We tackle this issue and propose a general method that considers any crowd animation and resolves existing residual collisions. To this end, we take a physics-based approach to model contacts between articulated characters. This enables the real-time synthesis of 3D high-density crowds with dozens of individuals that do not intersect each other, producing an unprecedented level of physical correctness in animations. Under the hood, we model each individual using a parametric human body incorporating a set of 3D proxies to approximate their volume. We then build a large system of articulated rigid bodies, and use an efficient physics-based approach to solve for individual body poses that do not collide with each other while maintaining the overall motion of the crowd. We first validate our approach objectively and quantitatively. We then explore relations between physical correctness and perceived realism based on an extensive user study that evaluates the relevance of solving contacts in dense crowds. Results demonstrate that our approach outperforms existing methods for crowd animation in terms of geometric accuracy and overall realism.","PeriodicalId":50913,"journal":{"name":"ACM Transactions on Graphics","volume":null,"pages":null},"PeriodicalIF":7.8,"publicationDate":"2024-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141920856","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

Conditional Mixture Path Guiding for Differentiable Rendering 用于可变渲染的条件混合路径引导

IF 7.8 1区计算机科学

ACM Transactions on Graphics Pub Date : 2024-07-19 DOI: 10.1145/3658133

Zhimin Fan, Pengcheng Shi, Mufan Guo, Ruoyu Fu, Yanwen Guo, Jie Guo

{"title":"Conditional Mixture Path Guiding for Differentiable Rendering","authors":"Zhimin Fan, Pengcheng Shi, Mufan Guo, Ruoyu Fu, Yanwen Guo, Jie Guo","doi":"10.1145/3658133","DOIUrl":"https://doi.org/10.1145/3658133","url":null,"abstract":"The efficiency of inverse optimization in physically based differentiable rendering heavily depends on the variance of Monte Carlo estimation. Despite recent advancements emphasizing the necessity of tailored differential sampling strategies, the general approaches remain unexplored.\u0000 In this paper, we investigate the interplay between local sampling decisions and the estimation of light path derivatives. Considering that modern differentiable rendering algorithms share the same path for estimating differential radiance and ordinary radiance, we demonstrate that conventional guiding approaches, conditioned solely on the last vertex, cannot attain this density. Instead, a mixture of different sampling distributions is required, where the weights are conditioned on all the previously sampled vertices in the path. To embody our theory, we implement a conditional mixture path guiding that explicitly computes optimal weights on the fly. Furthermore, we show how to perform positivization to eliminate sign variance and extend to scenes with millions of parameters.\u0000 To the best of our knowledge, this is the first generic framework for applying path guiding to differentiable rendering. Extensive experiments demonstrate that our method achieves nearly one order of magnitude improvements over state-of-the-art methods in terms of variance reduction in gradient estimation and errors of inverse optimization. The implementation of our proposed method is available at https://github.com/mollnn/conditional-mixture.","PeriodicalId":50913,"journal":{"name":"ACM Transactions on Graphics","volume":null,"pages":null},"PeriodicalIF":7.8,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141820899","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

A Fully-correlated Anisotropic Micrograin BSDF Model 完全相关的各向异性微晶 BSDF 模型

IF 7.8 1区计算机科学

ACM Transactions on Graphics Pub Date : 2024-07-19 DOI: 10.1145/3658224

Simon Lucas, Mickaël Ribardière, R. Pacanowski, Pascal Barla

引用次数: 0