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GIM3D plus: A labeled 3D dataset to design data-driven solutions for dressed humans GIM3D plus:一个标记的3D数据集，为穿着的人设计数据驱动的解决方案
IF 1.7 4区 计算机科学
Graphical Models Pub Date : 2023-10-01 DOI: 10.1016/j.gmod.2023.101187
Pietro Musoni , Simone Melzi , Umberto Castellani
{"title":"GIM3D plus: A labeled 3D dataset to design data-driven solutions for dressed humans","authors":"Pietro Musoni ,&nbsp;Simone Melzi ,&nbsp;Umberto Castellani","doi":"10.1016/j.gmod.2023.101187","DOIUrl":"10.1016/j.gmod.2023.101187","url":null,"abstract":"<div><p>Segmentation and classification of clothes in real 3D data are particularly challenging due to the extreme variation of their shapes, even among the same cloth category, induced by the underlying human subject. Several data-driven methods try to cope with this problem. Still, they must face the lack of available data to generalize to various real-world instances. For this reason, we present GIM3D plus (Garments In Motion 3D plus), a synthetic dataset of clothed 3D human characters in different poses. A physical simulation of clothes generates the over 5000 3D models in this dataset with different fabrics, sizes, and tightness, using animated human avatars representing different subjects in diverse poses. Our dataset comprises single meshes created to simulate 3D scans, with labels for the separate clothes and the visible body parts. We also provide an evaluation of the use of GIM3D plus as a training set on garment segmentation and classification tasks using state-of-the-art data-driven methods for both meshes and point clouds.</p></div>","PeriodicalId":55083,"journal":{"name":"Graphical Models","volume":"129 ","pages":"Article 101187"},"PeriodicalIF":1.7,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45694870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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
Neural style transfer for 3D meshes 3D网格的神经风格转移
IF 1.7 4区 计算机科学
Graphical Models Pub Date : 2023-10-01 DOI: 10.1016/j.gmod.2023.101198
Hongyuan Kang , Xiao Dong , Juan Cao , Zhonggui Chen
{"title":"Neural style transfer for 3D meshes","authors":"Hongyuan Kang ,&nbsp;Xiao Dong ,&nbsp;Juan Cao ,&nbsp;Zhonggui Chen","doi":"10.1016/j.gmod.2023.101198","DOIUrl":"https://doi.org/10.1016/j.gmod.2023.101198","url":null,"abstract":"<div><p>Style transfer is a popular research topic in the field of computer vision. In 3D stylization, a mesh model is deformed to achieve a specific geometric style. We explore a general neural style transfer framework for 3D meshes that can transfer multiple geometric styles from other meshes to the current mesh. Our stylization network is based on a pre-trained MeshNet model, from which content representation and Gram-based style representation are extracted. By constraining the similarity in content and style representation between the generated mesh and two different meshes, our network can generate a deformed mesh with a specific style while maintaining the content of the original mesh. Experiments verify the robustness of the proposed network and show the effectiveness of stylizing multiple models with one dedicated style mesh. We also conduct ablation experiments to analyze the effectiveness of our network.</p></div>","PeriodicalId":55083,"journal":{"name":"Graphical Models","volume":"129 ","pages":"Article 101198"},"PeriodicalIF":1.7,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49889739","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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
GSNet: Generating 3D garment animation via graph skinning network GSNet：通过图形蒙皮网络生成3D服装动画
IF 1.7 4区 计算机科学
Graphical Models Pub Date : 2023-10-01 DOI: 10.1016/j.gmod.2023.101197
Tao Peng , Jiewen Kuang , Jinxing Liang , Xinrong Hu , Jiazhe Miao , Ping Zhu , Lijun Li , Feng Yu , Minghua Jiang
{"title":"GSNet: Generating 3D garment animation via graph skinning network","authors":"Tao Peng ,&nbsp;Jiewen Kuang ,&nbsp;Jinxing Liang ,&nbsp;Xinrong Hu ,&nbsp;Jiazhe Miao ,&nbsp;Ping Zhu ,&nbsp;Lijun Li ,&nbsp;Feng Yu ,&nbsp;Minghua Jiang","doi":"10.1016/j.gmod.2023.101197","DOIUrl":"10.1016/j.gmod.2023.101197","url":null,"abstract":"<div><p>The goal of digital dress body animation is to produce the most realistic dress body animation possible. Although a method based on the same topology as the body can produce realistic results, it can only be applied to garments with the same topology as the body. Although the generalization-based approach can be extended to different types of garment templates, it still produces effects far from reality. We propose GSNet, a learning-based model that generates realistic garment animations and applies to garment types that do not match the body topology. We encode garment templates and body motions into latent space and use graph convolution to transfer body motion information to garment templates to drive garment motions. Our model considers temporal dependency and provides reliable physical constraints to make the generated animations more realistic. Qualitative and quantitative experiments show that our approach achieves state-of-the-art 3D garment animation performance.</p></div>","PeriodicalId":55083,"journal":{"name":"Graphical Models","volume":"129 ","pages":"Article 101197"},"PeriodicalIF":1.7,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47857326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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
GBGVD: Growth-based geodesic Voronoi diagrams GBGVD:基于生长的测地线Voronoi图
IF 1.7 4区 计算机科学
Graphical Models Pub Date : 2023-10-01 DOI: 10.1016/j.gmod.2023.101196
Yunjia Qi , Chen Zong , Yunxiao Zhang , Shuangmin Chen , Minfeng Xu , Lingqiang Ran , Jian Xu , Shiqing Xin , Ying He
{"title":"GBGVD: Growth-based geodesic Voronoi diagrams","authors":"Yunjia Qi ,&nbsp;Chen Zong ,&nbsp;Yunxiao Zhang ,&nbsp;Shuangmin Chen ,&nbsp;Minfeng Xu ,&nbsp;Lingqiang Ran ,&nbsp;Jian Xu ,&nbsp;Shiqing Xin ,&nbsp;Ying He","doi":"10.1016/j.gmod.2023.101196","DOIUrl":"https://doi.org/10.1016/j.gmod.2023.101196","url":null,"abstract":"<div><p>Given a set of generators, the geodesic Voronoi diagram (GVD) defines how the base surface is decomposed into separate regions such that each generator dominates a region in terms of geodesic distance to the generators. Generally speaking, each ordinary bisector point of the GVD is determined by two adjacent generators while each branching point of the GVD is given by at least three generators. When there are sufficiently many generators, straight-line distance serves as an effective alternative of geodesic distance for computing GVDs. However, for a set of sparse generators, one has to use exact or approximate geodesic distance instead, which requires a high computational cost to trace the bisectors and the branching points. We observe that it is easier to infer the branching points by stretching the ordinary segments than competing between wavefronts from different directions. Based on the observation, we develop an unfolding technique to compute the ordinary points of the GVD, as well as a growth-based technique to stretch the traced bisector segments such that they finally grow into a complete GVD. Experimental results show that our algorithm runs 3 times as fast as the state-of-the-art method at the same accuracy level.</p></div>","PeriodicalId":55083,"journal":{"name":"Graphical Models","volume":"129 ","pages":"Article 101196"},"PeriodicalIF":1.7,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49890151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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
PU-GAT: Point cloud upsampling with graph attention network PU-GAT:点云上采样与图关注网络
IF 1.7 4区 计算机科学
Graphical Models Pub Date : 2023-09-25 DOI: 10.1016/j.gmod.2023.101201
Xuan Deng, Cheng Zhang, Jian Shi, Zizhao Wu
{"title":"PU-GAT: Point cloud upsampling with graph attention network","authors":"Xuan Deng,&nbsp;Cheng Zhang,&nbsp;Jian Shi,&nbsp;Zizhao Wu","doi":"10.1016/j.gmod.2023.101201","DOIUrl":"https://doi.org/10.1016/j.gmod.2023.101201","url":null,"abstract":"<div><p>Point cloud upsampling has been extensively studied, however, the existing approaches suffer from the losing of structural information due to neglect of spatial dependencies between points. In this work, we propose PU-GAT, a novel 3D point cloud upsampling method that leverages graph attention networks to learn structural information over the baselines. Specifically, we first design a local–global feature extraction unit by combining spatial information and position encoding to mine the local spatial inter-dependencies across point features. Then, we construct an up-down-up feature expansion unit, which uses graph attention and GCN to enhance the ability of capturing local structure information. Extensive experiments on synthetic and real data have shown that our method achieves superior performance against previous methods quantitatively and qualitatively.</p></div>","PeriodicalId":55083,"journal":{"name":"Graphical Models","volume":"130 ","pages":"Article 101201"},"PeriodicalIF":1.7,"publicationDate":"2023-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49889743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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
Two-step techniques for accurate selection of small elements in VR environments 在VR环境中精确选择小元素的两步技术
IF 1.7 4区 计算机科学
Graphical Models Pub Date : 2023-07-01 DOI: 10.1016/j.gmod.2023.101183
Elena Molina, Pere-Pau Vázquez
{"title":"Two-step techniques for accurate selection of small elements in VR environments","authors":"Elena Molina,&nbsp;Pere-Pau Vázquez","doi":"10.1016/j.gmod.2023.101183","DOIUrl":"https://doi.org/10.1016/j.gmod.2023.101183","url":null,"abstract":"<div><p>One of the key interactions in 3D environments is target acquisition, which can be challenging when targets are small or in cluttered scenes. Here, incorrect elements may be selected, leading to frustration and wasted time. The accuracy is further hindered by the physical act of selection itself, typically involving pressing a button. This action reduces stability, increasing the likelihood of erroneous target acquisition. We focused on molecular visualization and on the challenge of selecting atoms, rendered as small spheres. We present two techniques that improve upon previous progressive selection techniques. They facilitate the acquisition of neighbors after an initial selection, providing a more comfortable experience compared to using classical ray-based selection, particularly with occluded elements. We conducted a pilot study followed by two formal user studies. The results indicated that our approaches were highly appreciated by the participants. These techniques could be suitable for other crowded environments as well.</p></div>","PeriodicalId":55083,"journal":{"name":"Graphical Models","volume":"128 ","pages":"Article 101183"},"PeriodicalIF":1.7,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49875410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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
Efficient collision detection using hybrid medial axis transform and BVH for rigid body simulation 基于混合中轴变换和BVH的刚体仿真高效碰撞检测
IF 1.7 4区 计算机科学
Graphical Models Pub Date : 2023-07-01 DOI: 10.1016/j.gmod.2023.101180
Xingxin Li, Shibo Song, Junfeng Yao, Hanyin Zhang, Rongzhou Zhou, Qingqi Hong
{"title":"Efficient collision detection using hybrid medial axis transform and BVH for rigid body simulation","authors":"Xingxin Li,&nbsp;Shibo Song,&nbsp;Junfeng Yao,&nbsp;Hanyin Zhang,&nbsp;Rongzhou Zhou,&nbsp;Qingqi Hong","doi":"10.1016/j.gmod.2023.101180","DOIUrl":"https://doi.org/10.1016/j.gmod.2023.101180","url":null,"abstract":"<div><p>Medial Axis Transform (MAT) has been recently adopted as the acceleration structure of broad-phase collision detection. Compared to traditional BVH-based methods, MAT can provide a high-fidelity volumetric approximation of 3D complex objects, resulting in higher collision culling efficiency. However, due to MAT’s non-hierarchical structure, it may be outperformed in collision-light scenarios because several cullings at the top level of a BVH may take a large number of cullings with MAT. We propose a collision detection method that combines MAT and BVH to address the above problem. Our technique efficiently culls collisions between dynamic and static objects. Experimental results show that our method has higher culling efficiency than pure BVH or MAT methods.</p></div>","PeriodicalId":55083,"journal":{"name":"Graphical Models","volume":"128 ","pages":"Article 101180"},"PeriodicalIF":1.7,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49875411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 robust workflow for b-rep generation from image masks 从图像蒙版生成b-rep的健壮工作流
IF 1.7 4区 计算机科学
Graphical Models Pub Date : 2023-07-01 DOI: 10.1016/j.gmod.2023.101174
Omar M. Hafez, Mark M. Rashid
{"title":"A robust workflow for b-rep generation from image masks","authors":"Omar M. Hafez,&nbsp;Mark M. Rashid","doi":"10.1016/j.gmod.2023.101174","DOIUrl":"https://doi.org/10.1016/j.gmod.2023.101174","url":null,"abstract":"<div><p>A novel approach to generating watertight, manifold boundary representations from noisy binary image masks of MRI or CT scans is presented. The method samples an input segmented image and locally approximates the material boundary. Geometric error metrics between the voxelated boundary and an approximating template surface are minimized, and boundary point/normals are correspondingly generated. Voronoi partitioning is employed to perform surface reconstruction on the resulting oriented point cloud. The method performs competitively against other approaches, both in comparisons of shape and volume error metrics to a canonical image mask, and in qualitative comparisons using noisy image masks from real scans. The framework readily admits enhancements for capturing sharp edges and corners. The approach robustly produces high-quality b-reps that may be inserted into an image-based meshing pipeline for purposes of physics-based simulation.</p></div>","PeriodicalId":55083,"journal":{"name":"Graphical Models","volume":"128 ","pages":"Article 101174"},"PeriodicalIF":1.7,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49875409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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: 1
SPIDER: A framework for processing, editing and presenting immersive high-resolution spherical indoor scenes SPIDER:用于处理、编辑和呈现沉浸式高分辨率球形室内场景的框架
IF 1.7 4区 计算机科学
Graphical Models Pub Date : 2023-07-01 DOI: 10.1016/j.gmod.2023.101182
M. Tukur , G. Pintore , E. Gobbetti , J. Schneider , M. Agus
{"title":"SPIDER: A framework for processing, editing and presenting immersive high-resolution spherical indoor scenes","authors":"M. Tukur ,&nbsp;G. Pintore ,&nbsp;E. Gobbetti ,&nbsp;J. Schneider ,&nbsp;M. Agus","doi":"10.1016/j.gmod.2023.101182","DOIUrl":"https://doi.org/10.1016/j.gmod.2023.101182","url":null,"abstract":"<div><p>Today’s Extended Reality (XR) applications that call for specific Diminished Reality (DR) strategies to hide specific classes of objects are increasingly using 360° cameras, which can capture entire areas in a single picture. In this work, we present an interactive-based image processing, editing and rendering system named <strong>SPIDER</strong>, that takes a spherical 360° indoor scene as input. The system is composed of a novel integrated deep learning architecture for extracting geometric and semantic information of full and empty rooms, based on gated and dilated convolutions, followed by a super-resolution module for improving the resolution of the color and depth signals. The obtained high resolution representations allow users to perform interactive exploration and basic editing operations on the reconstructed indoor scene, namely: (i) rendering of the scene in various modalities (point cloud, polygonal, wireframe) (ii) refurnishing (transferring portions of rooms) (iii) deferred shading through the usage of precomputed normal maps. These kinds of scene editing and manipulations can be used for assessing the inference from deep learning models and enable several Mixed Reality applications in areas such as furniture retails, interior designs, and real estates. Moreover, it can also be useful in data augmentation, arts, designs, and paintings. We report on the performance improvement of the various processing components on public domain spherical image indoor datasets.</p></div>","PeriodicalId":55083,"journal":{"name":"Graphical Models","volume":"128 ","pages":"Article 101182"},"PeriodicalIF":1.7,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49875412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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: 2
HMDO : Markerless multi-view hand manipulation capture with deformable objects 具有可变形对象的无标记多视图手操作捕获
IF 1.7 4区 计算机科学
Graphical Models Pub Date : 2023-05-01 DOI: 10.1016/j.gmod.2023.101178
Wei Xie, Zhipeng Yu, Zimeng Zhao, Binghui Zuo, Yangang Wang
{"title":"HMDO : Markerless multi-view hand manipulation capture with deformable objects","authors":"Wei Xie,&nbsp;Zhipeng Yu,&nbsp;Zimeng Zhao,&nbsp;Binghui Zuo,&nbsp;Yangang Wang","doi":"10.1016/j.gmod.2023.101178","DOIUrl":"https://doi.org/10.1016/j.gmod.2023.101178","url":null,"abstract":"<div><p>We construct the first markerless deformable interaction dataset recording interactive motions of the hands and deformable objects, called HMDO (Hand Manipulation with Deformable Objects). With our built multi-view capture system, it captures the deformable interactions with multiple perspectives, various object shapes, and diverse interactive forms. Our motivation is the current lack of hand and deformable object interaction datasets, as 3D hand and deformable object reconstruction is challenging. Mainly due to mutual occlusion, the interaction area is difficult to observe, the visual features between the hand and the object are entangled, and the reconstruction of the interaction area deformation is difficult. To tackle this challenge, we propose a method to annotate our captured data. Our key idea is to collaborate with estimated hand features to guide the object global pose estimation, and then optimize the deformation process of the object by analyzing the relationship between the hand and the object. Through comprehensive evaluation, the proposed method can reconstruct interactive motions of hands and deformable objects with high quality. HMDO currently consists of 21600 frames over 12 sequences. In the future, this dataset could boost the research of learning-based reconstruction of deformable interaction scenes.</p></div>","PeriodicalId":55083,"journal":{"name":"Graphical Models","volume":"127 ","pages":"Article 101178"},"PeriodicalIF":1.7,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49701216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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
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