ACM Transactions on Graphics (TOG)最新文献_第9页

CT2Hair: High-Fidelity 3D Hair Modeling using Computed Tomography CT2Hair:高保真3D头发建模使用计算机断层扫描

ACM Transactions on Graphics (TOG) Pub Date : 2023-07-26 DOI: 10.1145/3592106

Yuefan Shen, Shunsuke Saito, Ziyan Wang, O. Maury, Chenglei Wu, J. Hodgins, Youyi Zheng, Giljoo Nam

引用次数: 0

Inkjet 4D Print: Self-folding Tessellated Origami Objects by Inkjet UV Printing 喷墨4D打印:自折叠镶嵌折纸对象喷墨UV打印

ACM Transactions on Graphics (TOG) Pub Date : 2023-07-26 DOI: 10.1145/3592409

Koya Narumi, Kazuki Koyama, K. Suto, Yuta Noma, Hiroki Sato, Tomohiro Tachi, Masaaki Sugimoto, T. Igarashi, Yoshihiro Kawahara

引用次数: 2

Learning Physically Simulated Tennis Skills from Broadcast Videos 从广播视频中学习模拟网球技术

ACM Transactions on Graphics (TOG) Pub Date : 2023-07-26 DOI: 10.1145/3592408

Haotian Zhang, Ye Yuan, Viktor Makoviychuk, Yunrong Guo, S. Fidler, X. B. Peng, K. Fatahalian

{"title":"Learning Physically Simulated Tennis Skills from Broadcast Videos","authors":"Haotian Zhang, Ye Yuan, Viktor Makoviychuk, Yunrong Guo, S. Fidler, X. B. Peng, K. Fatahalian","doi":"10.1145/3592408","DOIUrl":"https://doi.org/10.1145/3592408","url":null,"abstract":"We present a system that learns diverse, physically simulated tennis skills from large-scale demonstrations of tennis play harvested from broadcast videos. Our approach is built upon hierarchical models, combining a low-level imitation policy and a high-level motion planning policy to steer the character in a motion embedding learned from broadcast videos. When deployed at scale on large video collections that encompass a vast set of examples of real-world tennis play, our approach can learn complex tennis shotmaking skills and realistically chain together multiple shots into extended rallies, using only simple rewards and without explicit annotations of stroke types. To address the low quality of motions extracted from broadcast videos, we correct estimated motion with physics-based imitation, and use a hybrid control policy that overrides erroneous aspects of the learned motion embedding with corrections predicted by the high-level policy. We demonstrate that our system produces controllers for physically-simulated tennis players that can hit the incoming ball to target positions accurately using a diverse array of strokes (serves, forehands, and backhands), spins (topspins and slices), and playing styles (one/two-handed backhands, left/right-handed play). Overall, our system can synthesize two physically simulated characters playing extended tennis rallies with simulated racket and ball dynamics. Code and data for this work is available at https://research.nvidia.com/labs/toronto-ai/vid2player3d/.","PeriodicalId":7077,"journal":{"name":"ACM Transactions on Graphics (TOG)","volume":"16 1","pages":"1 - 14"},"PeriodicalIF":0.0,"publicationDate":"2023-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83382899","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: 10

Winding Numbers on Discrete Surfaces 离散曲面上的圈数

ACM Transactions on Graphics (TOG) Pub Date : 2023-07-26 DOI: 10.1145/3592401

Nicole Feng, M. Gillespie, Keenan Crane

引用次数: 1

In-Timestep Remeshing for Contacting Elastodynamics 接触弹性动力学的时间步重网格

ACM Transactions on Graphics (TOG) Pub Date : 2023-07-26 DOI: 10.1145/3592428

Z. Ferguson, T. Schneider, D. Kaufman, Daniele Panozzo

{"title":"In-Timestep Remeshing for Contacting Elastodynamics","authors":"Z. Ferguson, T. Schneider, D. Kaufman, Daniele Panozzo","doi":"10.1145/3592428","DOIUrl":"https://doi.org/10.1145/3592428","url":null,"abstract":"We propose In-Timestep Remeshing, a fully coupled, adaptive meshing algorithm for contacting elastodynamics where remeshing steps are tightly integrated, implicitly, within the timestep solve. Our algorithm refines and coarsens the domain automatically by measuring physical energy changes within each ongoing timestep solve. This provides consistent, degree-of-freedom-efficient, productive remeshing that, by construction, is physics-aware and so avoids the errors, over-refinements, artifacts, per-example hand-tuning, and instabilities commonly encountered when remeshing with timestepping methods. Our in-timestep computation then ensures that each simulation step's output is both a converged stable solution on the updated mesh and a temporally consistent trajectory with respect to the model and solution of the last timestep. At the same time, the output is guaranteed safe (intersection- and inversion-free) across all operations. We demonstrate applications across a wide range of extreme stress tests with challenging contacts, sharp geometries, extreme compressions, large timesteps, and wide material stiffness ranges - all scenarios well-appreciated to challenge existing remeshing methods.","PeriodicalId":7077,"journal":{"name":"ACM Transactions on Graphics (TOG)","volume":"96 1","pages":"1 - 15"},"PeriodicalIF":0.0,"publicationDate":"2023-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73237598","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

Generalizing Shallow Water Simulations with Dispersive Surface Waves 用色散表面波推广浅水模拟

ACM Transactions on Graphics (TOG) Pub Date : 2023-07-26 DOI: 10.1145/3592098

S. Jeschke, C. Wojtan

引用次数: 0

ScanBot: Autonomous Reconstruction via Deep Reinforcement Learning ScanBot:基于深度强化学习的自主重建

ACM Transactions on Graphics (TOG) Pub Date : 2023-07-26 DOI: 10.1145/3592113

Hezhi Cao, Xia Xi, Guan Wu, Ruizhen Hu, Ligang Liu

{"title":"ScanBot: Autonomous Reconstruction via Deep Reinforcement Learning","authors":"Hezhi Cao, Xia Xi, Guan Wu, Ruizhen Hu, Ligang Liu","doi":"10.1145/3592113","DOIUrl":"https://doi.org/10.1145/3592113","url":null,"abstract":"Autoscanning of an unknown environment is the key to many AR/VR and robotic applications. However, autonomous reconstruction with both high efficiency and quality remains a challenging problem. In this work, we propose a reconstruction-oriented autoscanning approach, called ScanBot, which utilizes hierarchical deep reinforcement learning techniques for global region-of-interest (ROI) planning to improve the scanning efficiency and local next-best-view (NBV) planning to enhance the reconstruction quality. Given the partially reconstructed scene, the global policy designates an ROI with insufficient exploration or reconstruction. The local policy is then applied to refine the reconstruction quality of objects in this region by planning and scanning a series of NBVs. A novel mixed 2D-3D representation is designed for these policies, where a 2D quality map with tailored quality channels encoding the scanning progress is consumed by the global policy, and a coarse-to-fine 3D volumetric representation that embodies both local environment and object completeness is fed to the local policy. These two policies iterate until the whole scene has been completely explored and scanned. To speed up the learning of complex environmental dynamics and enhance the agent's memory for spatial-temporal inference, we further introduce two novel auxiliary learning tasks to guide the training of our global policy. Thorough evaluations and comparisons are carried out to show the feasibility of our proposed approach and its advantages over previous methods. Code and data are available at https://github.com/HezhiCao/Scanbot.","PeriodicalId":7077,"journal":{"name":"ACM Transactions on Graphics (TOG)","volume":"142 1","pages":"1 - 16"},"PeriodicalIF":0.0,"publicationDate":"2023-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80159647","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

Eventfulness for Interactive Video Alignment 交互式视频对齐的事件性

ACM Transactions on Graphics (TOG) Pub Date : 2023-07-26 DOI: 10.1145/3592118

Jiatian Sun, Longxiuling Deng, Triantafyllos Afouras, Andrew Owens, Abe Davis

{"title":"Eventfulness for Interactive Video Alignment","authors":"Jiatian Sun, Longxiuling Deng, Triantafyllos Afouras, Andrew Owens, Abe Davis","doi":"10.1145/3592118","DOIUrl":"https://doi.org/10.1145/3592118","url":null,"abstract":"Humans are remarkably sensitive to the alignment of visual events with other stimuli, which makes synchronization one of the hardest tasks in video editing. A key observation of our work is that most of the alignment we do involves salient localizable events that occur sparsely in time. By learning how to recognize these events, we can greatly reduce the space of possible synchronizations that an editor or algorithm has to consider. Furthermore, by learning descriptors of these events that capture additional properties of visible motion, we can build active tools that adapt their notion of eventfulness to a given task as they are being used. Rather than learning an automatic solution to one specific problem, our goal is to make a much broader class of interactive alignment tasks significantly easier and less time-consuming. We show that a suitable visual event descriptor can be learned entirely from stochastically-generated synthetic video. We then demonstrate the usefulness of learned and adaptive eventfulness by integrating it in novel interactive tools for applications including audio-driven time warping of video and the extraction and application of sound effects across different videos.","PeriodicalId":7077,"journal":{"name":"ACM Transactions on Graphics (TOG)","volume":"79 1","pages":"1 - 10"},"PeriodicalIF":0.0,"publicationDate":"2023-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81431585","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

Meso-Facets for Goniochromatic 3D Printing 用于角色3D打印的介面

ACM Transactions on Graphics (TOG) Pub Date : 2023-07-26 DOI: 10.1145/3592137

Lubna Abu Rmaileh, A. Brunton

{"title":"Meso-Facets for Goniochromatic 3D Printing","authors":"Lubna Abu Rmaileh, A. Brunton","doi":"10.1145/3592137","DOIUrl":"https://doi.org/10.1145/3592137","url":null,"abstract":"Goniochromatic materials and objects appear to have different colors depending on viewing direction. This occurs in nature, such as in wood or minerals, and in human-made objects such as metal and effect pigments. In this paper, we propose algorithms to control multi-material 3D printers to produce goniochromatic effects on arbitrary surfaces by procedurally augmenting the input surface with meso-facets, which allow distinct colors to be assigned to different viewing directions of the input surface while introducing minimal changes to that surface. Previous works apply only to 2D or 2.5D surfaces, require multiple fabrication technologies, or make considerable changes to the input surface and require special post-processing, whereas our approach requires a single fabrication technology and no special post-processing. Our framework is general, allowing different generating functions for both the shape and color of the facets. Working with implicit representations allows us to generate geometric features at the limit of device resolution without tessellation. We evaluate our approach for performance, showing negligible overhead compared to baseline color 3D print processing, and for goniochromatic quality.","PeriodicalId":7077,"journal":{"name":"ACM Transactions on Graphics (TOG)","volume":"1 1","pages":"1 - 12"},"PeriodicalIF":0.0,"publicationDate":"2023-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82969343","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: 2

Revisiting controlled mixture sampling for rendering applications 重新审视渲染应用程序的受控混合采样

ACM Transactions on Graphics (TOG) Pub Date : 2023-07-26 DOI: 10.1145/3592435

Qingqin Hua, Pascal Grittmann, P. Slusallek

引用次数: 0