随着功能强大的个人电脑和高端显卡的出现，虚拟世界、实时计算机动画和模拟、游戏出现了令人难以置信的发展。但与此同时，出现了新的、更便宜的虚拟现实设备，允许与这些实时虚拟世界甚至通过增强现实与现实世界进行交互。 3D 角色，尤其是虚拟人现在具有卓越的品质，可以在电影行业中使用它们。但这只是一个开始，随着人工智能和智能体技术的发展，这些角色将变得越来越自主甚至智能。他们将与动物和植物一起在虚拟生活中居住在虚拟世界中。

With the rapid advancement of personal computers and high-end graphics cards, significant progress has been made in the fields of virtual worlds, real-time computer animation, simulation, and gaming. At the same time, the emergence of new and more affordable virtual reality devices allows for interaction with these real-time virtual worlds, even integrating augmented reality with the real world. 3D characters, especially virtual humans, now possess exceptional quality and can be utilized in the film industry. However, this is just the beginning. As artificial intelligence and agent technologies continue to evolve, these characters will become increasingly autonomous and even intelligent. They will coexist with animals and plants in virtual life within these virtual worlds.

随着个人电脑和高端显卡的快速发展，虚拟世界、实时计算机动画、模拟和游戏领域取得了显著进步。同时，新型、价格更低的虚拟现实设备的出现，使得人们能够与这些实时虚拟世界进行交互，甚至通过增强现实与现实世界相结合。3D角色，特别是虚拟人，已经具备了卓越的品质，能够在电影行业中得到应用。然而，这仅仅是个开始。随着人工智能和智能体技术的不断进步，这些角色将变得越来越自主，甚至具备智能。它们将与动物和植物共同生活在虚拟世界中。

Computer Animation and Virtual Worlds

Abstract Parametric human modeling are limited to either single‐view frameworks or simple multi‐view frameworks, failing to fully leverage the advantages of easily trainable single‐view networks and the occlusion‐resistant capabilities of multi‐view images. The prevalent presence of object occlusion and self‐occlusion in real‐world scenarios leads to issues of robustness and accuracy in predicting human body parameters. Additionally, many methods overlook the spatial connectivity of human joints in the global estimation of model pose parameters, resulting in cumulative errors in continuous joint parameters.To address these challenges, we propose a flexible and efficient iterative decoding strategy. By extending from single‐view images to multi‐view video inputs, we achieve local‐to‐global optimization. We utilize attention mechanisms to capture the rotational dependencies between any node in the human body and all its ancestor nodes, thereby enhancing pose decoding capability. We employ a parameter‐level iterative fusion of multi‐view image data to achieve flexible integration of global pose information, rapidly obtaining appropriate projection features from different viewpoints, ultimately resulting in precise parameter estimation. Through experiments, we validate the effectiveness of the HIDE method on the Human3.6M and 3DPW datasets, demonstrating significantly improved visualization results compared to previous methods.

Weitao Lin

Jiguang Zhang

Weiliang Meng

Xianglong Liu

Xiaopeng Zhang

HIDE: Hierarchical iterative decoding enhancement for multi‐view 3D human parameter regression

HIDE：多视角三维人体参数回归的分层迭代解码增强

Abstract Point cloud semantic segmentation, a crucial research area in the 3D computer vision, lies at the core of many vision and robotics applications. Due to the irregular and disordered of the point cloud, however, the application of convolution on point clouds is challenging. In this article, we propose the “coordinate convolution,” which can effectively extract local structural information of the point cloud, to solve the inapplicability of conventional convolution neural network (CNN) structures on the 3D point cloud. The “coordinate convolution” is a projection operation of three planes based on the local coordinate system of each point. Specifically, we project the point cloud on three planes in the local coordinate system with a joint 2D convolution operation to extract its features. Additionally, we leverage a self‐encoding network based on image semantic segmentation U‐Net structure as the overall architecture of the point cloud semantic segmentation algorithm. The results demonstrate that the proposed method exhibited excellent performances for point cloud data sets corresponding to various scenes.

Zhaoxuan Zhang

Kun Li

Xuefeng Yin

Xinglin Piao

Yuxin Wang

Xin Yang

Baocai Yin

Point cloud semantic scene segmentation based on coordinate convolution

基于坐标卷积的点云语义场景分割

Abstract Research has shown that spatial perception is not only one of the essential abilities for success in science, technology, engineering, and mathematics (STEM), but is also closely related to the quality of human existence. However, for a variety of reasons, many students' spatial skills are less than ideal. In recent years, various video games are showing great potential as low‐cost but effective training tools to improve the educational level and cognitive skills. This paper presented a novel serious strategy game named Magic World . The game was designed to enhance children's spatial perception and motivation by using narrative, virtual contexts, and game mechanics that incorporate educational content with entertainment as a powerful extra‐curricular aid. A pilot study and evaluation experiment were conducted with primary school students ( N = 68) and the results showed that the training had a measurable positive impact on students' spatial ability. In addition, user experience surveys of the game showed that Magic World was considered a fun, challenging, and popular game for children.

Wenchen Guo

Shucheng Li

Zixun Zhang

Zhirui Chen

KuoHsiang Chang

Su Wang

Computer Animation &amp; Virtual

A “magic world” for children: Design and development of a serious game to improve spatial ability

儿童的“魔法世界”：提升空间能力的严肃游戏设计与开发

ABSTRACT Semantic segmentation is an important approach to present the perceptual semantic understanding of an image, which is of significant usage in various applications. Especially, body part segmentation is designed for segmenting body parts of human characters to assist different editing tasks, such as style editing, pose transfer, and animation production. Since segmentation requires pixel‐level precision in semantic labeling, classic heuristics‐based methods generally have unstable performance. With the deployment of deep learning, a great step has been taken in segmenting body parts of human characters in natural photographs. However, the existing models are purely trained on natural photographs and generally obtain incorrect segmentation results when applied on anime character images, due to the large visual gap between training data and testing data. In this article, we present a novel approach to achieving body part segmentation of cartoon characters via a pose‐based graph‐cut formulation. We demonstrate the use of the acquired body part segmentation map in various image editing tasks, including conditional generation, style manipulation, pose transfer, and video‐to‐anime.

Zhenhua Ou

Xueting Liu

Chengze Li

Zhenkun Wen

Ping Li

Zhijian Gao

Huisi Wu

Body Part Segmentation of Anime Characters

动漫角色身体部位分割

ABSTRACT Urban 3D models with high‐resolution details are the basis of various mixed reality and geographic information systems. Fast and accurate urban reconstruction from aerial photographs has attracted intense attention. Existing methods exploit multi‐view geometry information from landscape patterns with similar illumination conditions and terrain appearance. In practice, urban models become obsolete over time due to human activities. Mainstream reconstruction pipelines rebuild the whole scene even if the main part of them remains unchanged. This paper proposes a novel wrapping‐based incremental modeling framework to reuse existing models and renew them with new meshes efficiently. The paper illustrates a pose optimization method with illumination‐based augmentation and virtual bundle adjustment. Besides, a high‐performance wrapping‐based meshing method is proposed for fast reconstruction. Experimental results show that the proposed method can achieve higher performance and quality than state‐of‐the‐art methods.

Yuan Xiong

Zhong Zhou

Fast and Incremental 3D Model Renewal for Urban Scenes With Appearance Changes

城市场景外观变化下的快速增量三维模型更新

ABSTRACT A challenge in crowd simulation is to generate diverse pedestrian motions in virtual environments. Nowadays, there is a greater emphasis on the diversity and authenticity of pedestrian movements in crowd simulation, while most traditional models primarily focus on collision avoidance and motion continuity. Recent studies have enhanced realism through data‐driven approaches that exploit the movement patterns of pedestrians from real data for trajectory prediction. However, they have not taken into account the body‐part motions of pedestrians. Differing from these approaches, we innovatively utilize learning‐based character motion and physics animation to enhance the diversity of pedestrian motions in crowd simulation. The proposed method can provide a promising avenue for more diverse crowds and is realized by a novel framework that deeply integrates motion synthesis and physics animation with crowd simulation. The framework consists of three main components: the learning‐based motion generator, which is responsible for generating diverse character motions; the hybrid simulation, which ensures the physical realism of pedestrian motions; and the velocity‐based interface, which assists in integrating navigation algorithms with the motion generator. Experiments have been conducted to verify the effectiveness of the proposed method in different aspects. The visual results demonstrate the feasibility of our approach.

Yiwen Ma

Tingting Liu

Zhen Liu

Diverse Motions and Responses in Crowd Simulation

人群模拟中的多样运动与响应

ABSTRACT 3D facial motion retargeting has the advantage of capturing and recreating the nuances of human facial motions and speeding up the time‐consuming 3D facial animation process. However, the facial motion retargeting pipeline is limited in reflecting the facial motion's semantic information (i.e., meaning and intensity), especially when applied to nonhuman characters. The retargeting quality heavily relies on the target face rig, which requires time‐consuming preparation such as 3D scanning of human faces and modeling of blendshapes. In this paper, we propose a facial motion retargeting pipeline aiming to provide fast and semantically accurate retargeting results for diverse characters. The new framework comprises a target face parameterization module based on face anatomy and a compatible source motion interpretation module. From the quantitative and qualitative evaluations, we found that the proposed retargeting pipeline can naturally recreate the expressions performed by a motion capture subject in equivalent meanings and intensities, such semantic accuracy extends to the faces of nonhuman characters without labor‐demanding preparations.

ChangAn Zhu

Chris Joslin

A Facial Motion Retargeting Pipeline for Appearance Agnostic 3D Characters

面向外观无关的3D角色的面部运动重定向流程

ABSTRACT Conducting research on this subject remains relevant in light of the rapid development of technology and the emergence of new threats in cybersecurity, requiring constant updating of knowledge and protection methods. The purpose of the study is to identify effective front‐end security methods and technologies that help ensure the protection of user data and their privacy when using web applications or sites. A methodology that defines the steps and processes for effective front‐end security and user data protection is developed. The research identifies the primary security threats, including cross‐site scripting (XSS), cross‐site request forgery (CSRF), and SQL injections, and evaluates existing front‐end security methods such as Content Security Policy (CSP), HTTPS, authentication, and authorization mechanisms. The findings highlight the effectiveness of these measures in mitigating security risks, providing a clear assessment of their advantages and limitations. Key recommendations for developers include the integration of modern security protocols, regular updates, and comprehensive security training. This study offers practical insights to improve front‐end security and enhance user data protection in an evolving digital landscape.

Oleksandr Tkachenko

Vadim Goncharov

Przemysław Jatkiewicz

Enhancing Front‐End Security: Protecting User Data and Privacy in Web Applications

增强前端安全性：保护Web应用程序中的用户数据和隐私

Abbreviation	Computer Animation & Virtual
Journal Impact	0.71
Quartiles(Global)	COMPUTER SCIENCE, SOFTWARE ENGINEERING(Q4)

ISSN	1546-4261, 1546-427X
h-index	53

Publication Information	Publisher: John Wiley and Sons Ltd，Publishing cycle: Bimonthly，Journal Type: journal，Open Access Journals: No
Basic data	Year of publication: 2004，Proportion of original research papers: 100.00%，Self Citation Rate:11.10%， Gold OA Rate: 12.68%
Average review cycle	网友分享经验：较慢,6-12周
Average recruitment ratio	网友分享经验：容易

Computer Animation and Virtual Worlds

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HIDE: Hierarchical iterative decoding enhancement for multi‐view 3D human parameter regression

Point cloud semantic scene segmentation based on coordinate convolution

A “magic world” for children: Design and development of a serious game to improve spatial ability

Body Part Segmentation of Anime Characters

Fast and Incremental 3D Model Renewal for Urban Scenes With Appearance Changes

Body Part Segmentation of Anime Characters

Fast and Incremental 3D Model Renewal for Urban Scenes With Appearance Changes

Diverse Motions and Responses in Crowd Simulation

A Facial Motion Retargeting Pipeline for Appearance Agnostic 3D Characters

Enhancing Front‐End Security: Protecting User Data and Privacy in Web Applications