ACM Transactions on Graphics最新文献_第10页

DMHomo: Learning Homography with Diffusion Models DMHomo：利用扩散模型学习同构模型

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2024-03-11 DOI: 10.1145/3652207

Haipeng Li, Hai Jiang, Ao Luo, Ping Tan, Haoqiang Fan, Bing Zeng, Shuaicheng Liu

引用次数: 0

Joint Stroke Tracing and Correspondence for 2D Animation 二维动画的联合描边与对应

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2024-02-29 DOI: 10.1145/3649890

Haoran Mo, Chengying Gao, Ruomei Wang

引用次数: 0

A Dual-Particle Approach for Incompressible SPH Fluids 不可压缩 SPH 流体的双粒子方法

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2024-02-29 DOI: 10.1145/3649888

Shusen Liu, Xiaowei He, Yuzhong Guo, Yue Chang, Wencheng Wang

引用次数: 0

HQ3DAvatar: High Quality Implicit 3D Head Avatar HQ3DAvatar：高质量隐式 3D 头像

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2024-02-29 DOI: 10.1145/3649889

Kartik Teotia, Mallikarjun B R, Xingang Pan, Hyeongwoo Kim, Pablo Garrido, Mohamed Elgharib, Christian Theobalt

{"title":"HQ3DAvatar: High Quality Implicit 3D Head Avatar","authors":"Kartik Teotia, Mallikarjun B R, Xingang Pan, Hyeongwoo Kim, Pablo Garrido, Mohamed Elgharib, Christian Theobalt","doi":"10.1145/3649889","DOIUrl":"https://doi.org/10.1145/3649889","url":null,"abstract":"Multi-view volumetric rendering techniques have recently shown great potential in modeling and synthesizing high-quality head avatars. A common approach to capture full head dynamic performances is to track the underlying geometry using a mesh-based template or 3D cube-based graphics primitives. While these model-based approaches achieve promising results, they often fail to learn complex geometric details such as the mouth interior, hair, and topological changes over time. This paper presents a novel approach to building highly photorealistic digital head avatars. Our method learns a canonical space via an implicit function parameterized by a neural network. It leverages multiresolution hash encoding in the learned feature space, allowing for high-quality, faster training and high-resolution rendering. At test time, our method is driven by a monocular RGB video. Here, an image encoder extracts face-specific features that also condition the learnable canonical space. This encourages deformation-dependent texture variations during training. We also propose a novel optical flow based loss that ensures correspondences in the learned canonical space, thus encouraging artifact-free and temporally consistent renderings. We show results on challenging facial expressions and show free-viewpoint renderings at interactive real-time rates for a resolution of 480x270. Our method outperforms related approaches both visually and numerically. We will release our multiple-identity dataset to encourage further research.","PeriodicalId":50913,"journal":{"name":"ACM Transactions on Graphics","volume":"15 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140001070","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

Online Neural Path Guiding with Normalized Anisotropic Spherical Gaussians 用归一化各向异性球形高斯进行在线神经路径引导

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2024-02-28 DOI: 10.1145/3649310

Jiawei Huang, Akito Iizuka, Hajime Tanaka, Taku Komura, Yoshifumi Kitamura

{"title":"Online Neural Path Guiding with Normalized Anisotropic Spherical Gaussians","authors":"Jiawei Huang, Akito Iizuka, Hajime Tanaka, Taku Komura, Yoshifumi Kitamura","doi":"10.1145/3649310","DOIUrl":"https://doi.org/10.1145/3649310","url":null,"abstract":"Importance sampling techniques significantly reduce variance in physically-based rendering. In this paper we propose a novel online framework to learn the spatial-varying distribution of the full product of the rendering equation, with a single small neural network using stochastic ray samples. The learned distributions can be used to efficiently sample the full product of incident light. To accomplish this, we introduce a novel closed-form density model, called the Normalized Anisotropic Spherical Gaussian mixture, that can model a complex light field with a small number of parameters and that can be directly sampled. Our framework progressively renders and learns the distribution, without requiring any warm-up phases. With the compact and expressive representation of our density model, our framework can be implemented entirely on the GPU, allowing it to produce high-quality images with limited computational resources. The results show that our framework outperforms existing neural path guiding approaches and achieves comparable or even better performance than state-of-the-art online statistical path guiding techniques.","PeriodicalId":50913,"journal":{"name":"ACM Transactions on Graphics","volume":"27 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2024-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139994036","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

Importance Sampling BRDF Derivatives 重要度采样 BRDF 衍生物

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2024-02-21 DOI: 10.1145/3648611

Yash Belhe, Bing Xu, Sai Praveen Bangaru, Ravi Ramamoorthi, Tzu-Mao Li

{"title":"Importance Sampling BRDF Derivatives","authors":"Yash Belhe, Bing Xu, Sai Praveen Bangaru, Ravi Ramamoorthi, Tzu-Mao Li","doi":"10.1145/3648611","DOIUrl":"https://doi.org/10.1145/3648611","url":null,"abstract":"We propose a set of techniques to efficiently importance sample the derivatives of a wide range of BRDF models. In differentiable rendering, BRDFs are replaced by their differential BRDF counterparts which are real-valued and can have negative values. This leads to a new source of variance arising from their change in sign. Real-valued functions cannot be perfectly importance sampled by a positive-valued PDF, and the direct application of BRDF sampling leads to high variance. Previous attempts at antithetic sampling only addressed the derivative with the roughness parameter of isotropic microfacet BRDFs. Our work generalizes BRDF derivative sampling to anisotropic microfacet models, mixture BRDFs, Oren-Nayar, Hanrahan-Krueger, among other analytic BRDFs. Our method first decomposes the real-valued differential BRDF into a sum of single-signed functions, eliminating variance from a change in sign. Next, we importance sample each of the resulting single-signed functions separately. The first decomposition, positivization, partitions the real-valued function based on its sign, and is effective at variance reduction when applicable. However, it requires analytic knowledge of the roots of the differential BRDF, and for it to be analytically integrable too. Our key insight is that the single-signed functions can have overlapping support, which significantly broadens the ways we can decompose a real-valued function. Our product and mixture decompositions exploit this property, and they allow us to support several BRDF derivatives that positivization could not handle. For a wide variety of BRDF derivatives, our method significantly reduces the variance (up to 58x in some cases) at equal computation cost and enables better recovery of spatially varying textures through gradient-descent-based inverse rendering.","PeriodicalId":50913,"journal":{"name":"ACM Transactions on Graphics","volume":"80 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2024-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139915949","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

Self-Supervised High Dynamic Range Imaging: What Can Be Learned from a Single 8-bit Video? 自监督高动态范围成像：从单个 8 位视频中能学到什么？

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2024-02-20 DOI: 10.1145/3648570

Francesco Banterle, Demetris Marnerides, Thomas Bashford-Rogers, Kurt Debattista

引用次数: 0

GIPC: Fast and stable Gauss-Newton optimization of IPC barrier energy GIPC：快速稳定的工频阻挡能高斯-牛顿优化算法

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2024-01-27 DOI: 10.1145/3643028

Kemeng Huang, Floyd M. Chitalu, Huancheng Lin, Taku Komura

{"title":"GIPC: Fast and stable Gauss-Newton optimization of IPC barrier energy","authors":"Kemeng Huang, Floyd M. Chitalu, Huancheng Lin, Taku Komura","doi":"10.1145/3643028","DOIUrl":"https://doi.org/10.1145/3643028","url":null,"abstract":"Barrier functions are crucial for maintaining an intersection and inversion free simulation trajectory but existing methods which directly use distance can restrict implementation design and performance. We present an approach to rewriting the barrier function for arriving at an efficient and robust approximation of its Hessian. The key idea is to formulate a simplicial geometric measure of contact using mesh boundary elements, from which analytic eigensystems are derived and enhanced with filtering and stiffening terms that ensure robustness with respect to the convergence of a Project-Newton solver. A further advantage of our rewriting of the barrier function is that it naturally caters to the notorious case of nearly-parallel edge-edge contacts for which we also present a novel analytic eigensystem. Our approach is thus well suited for standard second order unconstrained optimization strategies for resolving contacts, minimizing nonlinear nonconvex functions where the Hessian may be indefinite. The efficiency of our eigensystems alone yields a 3 × speedup over the standard IPC barrier formulation. We further apply our analytic proxy eigensystems to produce an entirely GPU-based implementation of IPC with significant further acceleration.","PeriodicalId":50913,"journal":{"name":"ACM Transactions on Graphics","volume":"56 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2024-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139568249","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

Spectral Total-Variation Processing of Shapes - Theory and Applications 形状的光谱总变化处理 - 理论与应用

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2024-01-26 DOI: 10.1145/3641845

Jonathan Brokman, Martin Burger, Guy Gilboa

{"title":"Spectral Total-Variation Processing of Shapes - Theory and Applications","authors":"Jonathan Brokman, Martin Burger, Guy Gilboa","doi":"10.1145/3641845","DOIUrl":"https://doi.org/10.1145/3641845","url":null,"abstract":"We present a comprehensive analysis of total variation (TV) on non-Euclidean domains and its eigenfunctions. We specifically address parameterized surfaces, a natural representation of the shapes used in 3D graphics. Our work sheds new light on the celebrated Beltrami and Anisotropic TV flows, and explains experimental findings from recent years on shape spectral TV [Fumero et al. 2020] and adaptive anisotropic spectral TV [Biton and Gilboa 2022]. A new notion of convexity on surfaces is derived by characterizing structures that are stable throughout the TV flow, performed on surfaces. We establish and numerically demonstrate quantitative relationships between TV, area, eigenvalue, and eigenfunctions of the TV operator on surfaces. Moreover, we expand the shape spectral TV toolkit to include zero-homogeneous flows, leading to efficient and versatile shape processing methods. These methods are exemplified through applications in smoothing, enhancement, and exaggeration filters. We introduce a novel method which, for the first time, addresses the shape deformation task using TV. This deformation technique is characterized by the concentration of deformation along geometrical bottlenecks, shown to coincide with the discontinuities of eigenfunctions. Overall, our findings elucidate recent experimental observations in spectral TV, provide a diverse framework for shape filtering, and present the first TV-based approach to shape deformation.","PeriodicalId":50913,"journal":{"name":"ACM Transactions on Graphics","volume":"38 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2024-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139565693","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

NeuralVDB: High-resolution Sparse Volume Representation using Hierarchical Neural Networks NeuralVDB：利用层次神经网络进行高分辨率稀疏体表示

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2024-01-23 DOI: 10.1145/3641817

Doyub Kim, Minjae Lee, Ken Museth

{"title":"NeuralVDB: High-resolution Sparse Volume Representation using Hierarchical Neural Networks","authors":"Doyub Kim, Minjae Lee, Ken Museth","doi":"10.1145/3641817","DOIUrl":"https://doi.org/10.1145/3641817","url":null,"abstract":"We introduce NeuralVDB, which improves on an existing industry standard for efficient storage of sparse volumetric data, denoted VDB [Museth 2013], by leveraging recent advancements in machine learning. Our novel hybrid data structure can reduce the memory footprints of VDB volumes by orders of magnitude, while maintaining its flexibility and only incurring small (user-controlled) compression errors. Specifically, NeuralVDB replaces the lower nodes of a shallow and wide VDB tree structure with multiple hierarchical neural networks that separately encode topology and value information by means of neural classifiers and regressors respectively. This approach is proven to maximize the compression ratio while maintaining the spatial adaptivity offered by the higher-level VDB data structure. For sparse signed distance fields and density volumes, we have observed compression ratios on the order of 10 × to more than 100 × from already compressed VDB inputs, with little to no visual artifacts. Furthermore, NeuralVDB is shown to offer more effective compression performance compared to other neural representations such as Neural Geometric Level of Detail [Takikawa et al. 2021], Variable Bitrate Neural Fields [Takikawa et al. 2022a], and Instant Neural Graphics Primitives [Müller et al. 2022]. Finally, we demonstrate how warm-starting from previous frames can accelerate training, i.e., compression, of animated volumes as well as improve temporal coherency of model inference, i.e., decompression.","PeriodicalId":50913,"journal":{"name":"ACM Transactions on Graphics","volume":"65 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2024-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139522653","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