ACM Transactions on Graphics最新文献

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2025-10-07 DOI: 10.1145/3770578

Sacha Jungerman, Aryan Garg, Mohit Gupta

引用次数: 0

CHOICE: Coordinated Human-Object Interaction in Cluttered Environments for Pick-and-Place Actions 选择：在混乱的拾取和放置动作环境中协调人机交互

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2025-10-02 DOI: 10.1145/3770746

Jintao Lu, He Zhang, Yuting Ye, Takaaki Shiratori, Sebastian Starke, Taku Komura

{"title":"CHOICE: Coordinated Human-Object Interaction in Cluttered Environments for Pick-and-Place Actions","authors":"Jintao Lu, He Zhang, Yuting Ye, Takaaki Shiratori, Sebastian Starke, Taku Komura","doi":"10.1145/3770746","DOIUrl":"https://doi.org/10.1145/3770746","url":null,"abstract":"Animating human-scene interactions such as picking and placing a wide range of objects with different geometries is a challenging task, especially in a cluttered environment where interactions with complex articulated containers are involved. The main difficulty lies in the sparsity of the motion data compared to the wide variation of the objects and environments, as well as the poor availability of transition motions between different actions, increasing the complexity of the generalization to arbitrary conditions. To cope with this issue, we develop a system that tackles the interaction synthesis problem as a hierarchical goal-driven task. Firstly, we develop a bimanual scheduler that plans a set of keyframes for simultaneously controlling the two hands to efficiently achieve the pick-and-place task from an abstract goal signal such as the target object selected by the user. Next, we develop a neural implicit planner that generates hand trajectories to guide reaching and leaving motions across diverse object shapes/types and obstacle layouts. Finally, we propose a linear dynamic model for our DeepPhase controller that incorporates a Kalman filter to enable smooth transitions in the frequency domain, resulting in a more realistic and effective multi-objective control of the character. Our system can synthesize a rich variety of natural pick-and-place movements that adapt to different object geometries, container articulations, and scene layouts.","PeriodicalId":50913,"journal":{"name":"ACM Transactions on Graphics","volume":"55 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2025-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145203278","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

RemixFusion: Residual-based Mixed Representation for Large-scale Online RGB-D Reconstruction RemixFusion：基于残差的大规模在线RGB-D重建混合表示

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2025-09-19 DOI: 10.1145/3769007

Yuqing Lan, Chenyang Zhu, Shuaifeng Zhi, Jiazhao Zhang, Zhoufeng Wang, Renjiao Yi, Yijie Wang, Kai Xu

{"title":"RemixFusion: Residual-based Mixed Representation for Large-scale Online RGB-D Reconstruction","authors":"Yuqing Lan, Chenyang Zhu, Shuaifeng Zhi, Jiazhao Zhang, Zhoufeng Wang, Renjiao Yi, Yijie Wang, Kai Xu","doi":"10.1145/3769007","DOIUrl":"https://doi.org/10.1145/3769007","url":null,"abstract":"The introduction of the neural implicit representation has notably propelled the advancement of online dense reconstruction techniques. Compared to traditional explicit representations, such as TSDF, it substantially improves the mapping completeness and memory efficiency. However, the lack of reconstruction details and the time-consuming learning of neural representations hinder the widespread application of neural-based methods to large-scale online reconstruction. We introduce RemixFusion, a novel residual-based mixed representation for scene reconstruction and camera pose estimation dedicated to high-quality and large-scale online RGB-D reconstruction. In particular, we propose a residual-based map representation comprised of an explicit coarse TSDF grid and an implicit neural module that produces residuals representing fine-grained details to be added to the coarse grid. Such mixed representation allows for detail-rich reconstruction with bounded time and memory budget, contrasting with the overly-smoothed results by the purely implicit representations, thus paving the way for high-quality camera tracking. Furthermore, we extend the residual-based representation to handle multi-frame joint pose optimization via bundle adjustment (BA). In contrast to the existing methods, which optimize poses directly, we opt to optimize pose changes. Combined with a novel technique for adaptive gradient amplification, our method attains better optimization convergence and global optimality. Furthermore, we adopt a local moving volume to factorize the whole mixed scene representation with a divide-and-conquer design to facilitate efficient online learning in our residual-based framework. Extensive experiments demonstrate that our method surpasses all state-of-the-art ones, including those based either on explicit or implicit representations, in terms of the accuracy of both mapping and tracking on large-scale scenes.","PeriodicalId":50913,"journal":{"name":"ACM Transactions on Graphics","volume":"38 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145089117","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

Local Surface Parameterizations via Smoothed Geodesic Splines 通过光滑测地线样条进行局部曲面参数化

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2025-09-17 DOI: 10.1145/3767323

Abhishek Madan, David Levin

引用次数: 0

Many-Worlds Inverse Rendering 多世界逆向渲染

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2025-09-12 DOI: 10.1145/3767318

Ziyi Zhang, Nicolas Roussel, Wenzel Jakob

引用次数: 0

A fast, efficient, and robust feature protected denoising method 一种快速、高效、鲁棒的特征保护去噪方法

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2025-09-03 DOI: 10.1145/3765902

Mengyu Luo, Jian Wang

引用次数: 0

SymX: Energy-based Simulation from Symbolic Expressions SymX：基于符号表达式的能量模拟

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2025-09-02 DOI: 10.1145/3764928

José Fernández-Fernández, Fabian Löschner, Lukas Westhofen, Andreas Longva, Jan Bender

{"title":"SymX: Energy-based Simulation from Symbolic Expressions","authors":"José Fernández-Fernández, Fabian Löschner, Lukas Westhofen, Andreas Longva, Jan Bender","doi":"10.1145/3764928","DOIUrl":"https://doi.org/10.1145/3764928","url":null,"abstract":"Optimization time integrators are effective at solving complex multi-physics problems including deformable solids with non-linear material models, contact with friction, strain limiting, etc. For challenging problems, Newton-type optimizers are often used, which necessitates first- and second-order derivatives of the global non-linear objective function. Manually differentiating, implementing, testing, optimizing, and maintaining the resulting code is extremely time-consuming, error-prone, and precludes quick changes to the model, even when using tools that assist with parts of such pipeline. We present SymX, an open source framework that computes the required derivatives of the different energy contributions by symbolic differentiation, generates optimized code, compiles it on-the-fly, and performs the global assembly. The user only has to provide the symbolic expression of each energy for a single representative element in its corresponding discretization and our system will determine the assembled derivatives for the whole simulation. We demonstrate the versatility of SymX in complex simulations featuring different non-linear materials, high-order finite elements, rigid body systems, adaptive discretizations, frictional contact, and coupling of multiple interacting physical systems. SymX’s derivatives offer performance on par with SymPy, an established off-the-shelf symbolic engine, and produces simulations at least one order of magnitude faster than TinyAD, an alternative state-of-the-art integral solution.","PeriodicalId":50913,"journal":{"name":"ACM Transactions on Graphics","volume":"24 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144930903","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 Neural Reflectance Field Model for Accurate Relighting in RTI Applications RTI应用中精确重照明的神经反射场模型

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2025-08-28 DOI: 10.1145/3759452

Shambel Fente Mengistu, Filippo Bergamasco, Mara Pistellato

{"title":"A Neural Reflectance Field Model for Accurate Relighting in RTI Applications","authors":"Shambel Fente Mengistu, Filippo Bergamasco, Mara Pistellato","doi":"10.1145/3759452","DOIUrl":"https://doi.org/10.1145/3759452","url":null,"abstract":"Reflectance Transformation Imaging (RTI) is a computational photography technique in which an object is acquired from a fixed point-of-view with different light directions. The aim is to estimate the light transport function at each point so that the object can be interactively relighted in a physically-accurate way, revealing its surface characteristics. In this paper, we propose a novel RTI approach describing surface reflectance as an implicit neural representation acting as a ”relightable image” for a specific object. We propose to represent the light transport function with a Neural Reflectance Field (NRF) model, feeding it with pixel coordinates, light direction, and a latent vector encoding the per-pixel reflectance in a neighbourhood. These vectors, computed during training, allow a more accurate relighting than a pure implicit representation (i.e., relying only on positional encoding) enabling the NRF to handle complex surface shadings. Moreover, they can be efficiently stored with the learned NRF for compression and transmission. As an additional contribution, we propose a novel synthetic dataset containing objects of various shapes and materials created with a physically based rendering software. An extensive experimental section shows that the proposed NRF accurately models the light transport function for challenging datasets in synthetic and real-world scenarios.","PeriodicalId":50913,"journal":{"name":"ACM Transactions on Graphics","volume":"27 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144915648","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

PatchEX: High-Quality Real-Time Temporal Supersampling through Patch-based Parallel Extrapolation PatchEX：基于patch的并行外推的高质量实时时间超采样

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2025-08-12 DOI: 10.1145/3759247

Akanksha Dixit, Smruti R. Sarangi

{"title":"PatchEX: High-Quality Real-Time Temporal Supersampling through Patch-based Parallel Extrapolation","authors":"Akanksha Dixit, Smruti R. Sarangi","doi":"10.1145/3759247","DOIUrl":"https://doi.org/10.1145/3759247","url":null,"abstract":"High-refresh rate displays have become very popular in recent years due to the need for superior visual quality in gaming, professional displays and specialized applications such as medical imaging. However, high-refresh rate displays alone do not guarantee a superior visual experience; the GPU needs to render frames at a matching rate. Otherwise, we observe disconcerting visual artifacts such as screen tearing and stuttering. Real-time frame generation is an effective technique to increase frame rates by predicting new frames from other rendered frames. There are two methods in this space: interpolation and extrapolation. Interpolation-based methods provide good image quality at the cost of a higher runtime because they also require the next rendered frame. On the other hand, extrapolation methods are much faster at the cost of quality. This paper introduces PatchEX , a novel frame extrapolation method that aims to provide the quality of interpolation at the speed of extrapolation. It smartly segments each frame into foreground and background regions and employs a novel neural network to generate the final extrapolated frame. Additionally, a wavelet transform (WT)-based filter pruning technique is applied to compress the network, significantly reducing the runtime of the extrapolation process. Our results demonstrate that PatchEX achieves a 61.32% and 49.21% improvement in PSNR over the latest extrapolation methods ExtraNet and ExtraSS, respectively, while being 3 × and 2.6 × faster, respectively.","PeriodicalId":50913,"journal":{"name":"ACM Transactions on Graphics","volume":"19 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144850851","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

Iris3D: 3D Generation via Synchronized Diffusion Distillation Iris3D：通过同步扩散蒸馏生成3D

IF 6.2 1区计算机科学

ACM Transactions on Graphics Pub Date : 2025-08-07 DOI: 10.1145/3759249

Yixun Liang, Weiyu Li, Rui Chen, Fei-Peng Tian, Jiarui Liu, Ying-Cong Chen, Ping Tan, Xiao-Xiao Long

{"title":"Iris3D: 3D Generation via Synchronized Diffusion Distillation","authors":"Yixun Liang, Weiyu Li, Rui Chen, Fei-Peng Tian, Jiarui Liu, Ying-Cong Chen, Ping Tan, Xiao-Xiao Long","doi":"10.1145/3759249","DOIUrl":"https://doi.org/10.1145/3759249","url":null,"abstract":"We introduce Iris3D, a novel 3D content generation system that generates vivid textures and detailed 3D shapes while preserving the input information. Our system integrates a Multi-View Large Reconstruction Model (MVLRM [25]) to generate a coarse 3D mesh and introduces a novel optimization scheme called Synchronized Diffusion Distillation (SDD) for refinement. Unlike previous refined methods based on Score Distillation Sampling (SDS), which suffer from unstable optimization and geometric over-smoothing due to ambiguities across different views and modalities, our method effectively distills consistent multi-view and multi-modal priors from 2D diffusion models in a training-free manner. This enables robust optimization of 3D representations. Additionally, because SDD is training-free, it preserves the diffusion’s prior knowledge and mitigates potential degradation. This characteristic makes it highly compatible with advanced 2D diffusion techniques like IP-Adapters and ControlNet, allowing for more controllable 3D generation with additional conditioning signals. Experiments demonstrate that our method produces high-quality 3D results with plausible textures and intricate geometric details.","PeriodicalId":50913,"journal":{"name":"ACM Transactions on Graphics","volume":"55 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2025-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144792842","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