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Journal articles on the topic 'Photo-realistic computer graphics'

Author: Grafiati

Published: 5 June 2025

Last updated: 15 July 2025

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1

Garvey, Gregory P. "Life Drawing and 3D Figure Modeling with MAYA: Developing Alternatives to Photo-Realistic Modeling." Leonardo 35, no. 3 (2002): 303–10. http://dx.doi.org/10.1162/002409402760105325.

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This paper discusses the organization and motivation for a workshop devoted to the experimental use of 3D computer graphics to model the human figure. The workshop introduced a simple technique for modeling a leg by lofting a series of circles into the appropriate shape using sketches drawn from life. This approach links the expressive world of drawing to the impersonal mechanical tasks of computer modeling. The workshop also served as an introduction to 3D modeling and the MAYA 3D Computer Graphics Software Graphical User Interface. The drawing exercises of Kimon Nicolaïdes are discussed and

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Yang, Shunyu. "NeRF-based Real-Time Rendering Photo-Realistic Graphics Methods Review." Transactions on Computer Science and Intelligent Systems Research 5 (August 12, 2024): 397–403. http://dx.doi.org/10.62051/26c21r61.

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Recently, the publication of the Neural Radiance Field (NeRF) has sparked a surge in further research, unveiling a wealth of innovative solutions in related domains. With its potent predictive capabilities and operational efficiency, neural networks have addressed the traditional trade-off dilemma, enabling real-time rendering at state-of-the-art (SOTA) quality. This breakthrough has introduced a novel rendering approach in computer graphics (CG) and unlocked fresh opportunities for real-time applications such as video games, augmented reality (AR), and virtual reality (VR). This paper aims to

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J, Benjamin Douglas. "Analysis of Ray Tracing Methodology and Techniques and its Distinction from other Render Models." International Journal for Research in Applied Science and Engineering Technology 10, no. 8 (2022): 1205–9. http://dx.doi.org/10.22214/ijraset.2022.46397.

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Abstract: In 3D computer-generated graphics, ray tracing is a form of rendering technique for calculating light transport for the purpose of giving a photo-realistic image. This survey paper mainly focuses on the brief working of ray tracing methodology and various techniques available to achieve this. This helps to understand one how ray tracing can be applied in the field of computer graphics to produce stunning realistic renders. At present time ray tracing is primarily available for gaming (real-time ray tracing) and also for visual effects in cinema industry. This paper also gives a detai

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NAKAMAE, EIHACHIRO. "AN OVERVIEW OF PHOTO-REALISM FOR OUTDOOR SCENES." International Journal of Image and Graphics 01, no. 01 (2001): 27–43. http://dx.doi.org/10.1142/s0219467801000049.

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This paper examines rendering techniques of outdoor scenes intended for use in visual environmental assessment using computer graphics and/or video sequence images and discusses their advantages and limitations. The techniques are classified into the following three categories. First, rendering techniques of computer generated images and montages creating a photo-realistic landscape image based on optical phenomena are introduced; these are quite useful for careful and detailed study of landscapes. Second, a method for creating a precise panoramic image from panned video sequence images taken

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Sun, Di, Rui Zhan, Jiawan Zhang, and Gang Pan. "Realistic Story Visualization from Online Photo Collections." Journal of Computer-Aided Design & Computer Graphics 30, no. 8 (2018): 1479. http://dx.doi.org/10.3724/sp.j.1089.2018.16765.

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Baskar, Chanthini, Guga Priya Govindasamy, Sasithradevi Anbalagan, and Sindha Mohamed Mansoor Roomi. "Computer Graphic and Photographic Image Classification Using Transfer Learning Approach." Traitement du Signal 39, no. 4 (2022): 1267–73. http://dx.doi.org/10.18280/ts.390419.

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Advancement in information and communication technology has led to tremendous development in graphics techniques. Evolving multimedia tools are used to generate high quality Computer Graphics (CG) images. These images have wide applications in domains like video gaming, augmented reality, and virtual reality and many other. Computer graphic images are also used illegally in criminal activities. This article proposes an effective transfer learning approach to classify CG and Photographic (PG) images available in small scale dataset. Initially, pre-trained models such as AlexNet, GoogleNet, ResN

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Shin, Yoon-Seo, and Jeong-Hyun Lee. "Axonometric projection Study for Multilateral Expression of Art Hair." Korean Society of Beauty and Art 24, no. 2 (2023): 265–80. http://dx.doi.org/10.18693/jksba.2023.24.2.265.

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This study intends to explore masterpieces which are characteristic concerning ancient Greek and Roman mythologies and to analyze the underlying meanings behind the allergories of the Gods and Goddesses of Mount Olympus. With the help of computer graphics and 2D Axonometric projection, this study to realize the devised hair artwork by drawing inspiration form the assessed allegories. The significance of computer graphics id that they can be used to create pieces whose expression by hand is simply impossible and try different types of expressions with various new expressive techniques that may

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Eljadid, Mahmoud Geat, Amar Aggoun, and Osama H. Attallah. "Near to Real-time Computer Generation of 3D Holoscopic Images." International Science and Technology Journal 34, no. 1 (2024): 1–17. http://dx.doi.org/10.62341/namo2725.

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Generating a truly photo-realistic 3D real-time view capability in an ergonomic and cost effective manner is a crucial engineering challenge. In this paper, the advanced integral imaging methodology is proposed that is based on microlens arrays to generate 3D Holoscopic images by the intersection ray bundle that defines each image point in the associated scene at the correct spatial place. The core idea of the novel algorithm reported in this paper is to accelerate the computer generation of photo-realistic still 3D Holoscopic images based on multiprocessor ray-traced system. Consequently a si

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Chandran, Prashanth, Sebastian Winberg, Gaspard Zoss, et al. "Rendering with style." ACM Transactions on Graphics 40, no. 6 (2021): 1–14. http://dx.doi.org/10.1145/3478513.3480509.

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For several decades, researchers have been advancing techniques for creating and rendering 3D digital faces, where a lot of the effort has gone into geometry and appearance capture, modeling and rendering techniques. This body of research work has largely focused on facial skin, with much less attention devoted to peripheral components like hair, eyes and the interior of the mouth. As a result, even with the best technology for facial capture and rendering, in most high-end productions a lot of artist time is still spent modeling the missing components and fine-tuning the rendering parameters

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Deng, Xiaoming, Yinda Zhang, Jian Shi, et al. "Hand Pose Understanding With Large-Scale Photo-Realistic Rendering Dataset." IEEE Transactions on Image Processing 30 (2021): 4275–90. http://dx.doi.org/10.1109/tip.2021.3070439.

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Tadeja, Slawomir Konrad, Wojciech Rydlewicz, Yupu Lu, et al. "Measurement and Inspection of Photo-Realistic 3-D VR Models." IEEE Computer Graphics and Applications 41, no. 6 (2021): 143–51. http://dx.doi.org/10.1109/mcg.2021.3114955.

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Verbiest, F., G. Willems, and L. Van Gool. "Image-based rendering for photo-realistic visualization." Virtual and Physical Prototyping 1, no. 1 (2006): 19–30. http://dx.doi.org/10.1080/17452750500283533.

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Liu, Xiaoju. "An overview of Neural Radiance Fields." Applied and Computational Engineering 45, no. 1 (2024): 1–6. http://dx.doi.org/10.54254/2755-2721/45/20241016.

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Synthesizing controllable, photo-realistic images and videos is one of the fundamental goals of computer graphics. Neural rendering is a rapidly emerging field in image synthesis that allows a compact representation of scenes, and by utilizing neural networks, rendering can be learned from existing observations. Neural Radiance Fields (NeRF) implement an effective combination of Neural Fields and the graphics component Volume rendering. It achieves the first photo-level view synthesis effect using an implicit representation. Unlike previous approaches, NeRF chooses Volume as an intermediate re

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Cui, Ziwei. "Application of Line Integral Convolution Techniques in the Generation of Fine Art Painting Effects." Mobile Information Systems 2022 (July 4, 2022): 1–7. http://dx.doi.org/10.1155/2022/6872214.

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Since the 1980s, nonrealistic drawing techniques have become one of the main focuses of research in computer graphics. In recent years, with the rapid development of computer graphics, nonrealistic drawing techniques have become capable of rendering any digital image into an image with an alternative artistic style. As a result, many scholars have focused on the pencil sketch style. Against this backdrop, research into how to create more realistic art drawings has become a hot topic. Although the rapid development of computer technology has led to advances in art drawing techniques, traditiona

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Ma, Li, Xiaoyu Li, Jing Liao, et al. "Neural Parameterization for Dynamic Human Head Editing." ACM Transactions on Graphics 41, no. 6 (2022): 1–15. http://dx.doi.org/10.1145/3550454.3555494.

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Implicit radiance functions emerged as a powerful scene representation for reconstructing and rendering photo-realistic views of a 3D scene. These representations, however, suffer from poor editability. On the other hand, explicit representations such as polygonal meshes allow easy editing but are not as suitable for reconstructing accurate details in dynamic human heads, such as fine facial features, hair, teeth, and eyes. In this work, we present Neural Parameterization (NeP), a hybrid representation that provides the advantages of both implicit and explicit methods. NeP is capable of photo-

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Gong, Han, Graham D. Finlayson, Robert B. Fisher, and Fufu Fang. "3D color homography model for photo-realistic color transfer re-coding." Visual Computer 35, no. 3 (2017): 323–33. http://dx.doi.org/10.1007/s00371-017-1462-x.

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Halaguru, Basavarajappa Basanth Kumar, and Rajanna Chennamma Haranahalli. "Dataset for classification of computer graphic images and photographic images." International Journal of Artificial Intelligence (IJ-AI) 11, no. 1 (2022): 137–47. https://doi.org/10.11591/ijai.v11.i1.pp137-147.

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The recent advancements in computer graphics (CG) image rendering techniques have made it easy for the content creators to produce high quality computer graphics similar to photographic images (PG) confounding the most naïve users. Such images used with negative intent, cause serious problems to the society. In such cases, proving the authenticity of an image is a big challenge in digital image forensics due to high photo-realism of CG images. Existing datasets used to assess the performance of classification models are lacking with: (i) larger dataset size, (ii) diversified image content

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Xue, Yuan, Yuan-Chen Guo, Han Zhang, Tao Xu, Song-Hai Zhang, and Xiaolei Huang. "Deep image synthesis from intuitive user input: A review and perspectives." Computational Visual Media 8, no. 1 (2021): 3–31. http://dx.doi.org/10.1007/s41095-021-0234-8.

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AbstractIn many applications of computer graphics, art, and design, it is desirable for a user to provide intuitive non-image input, such as text, sketch, stroke, graph, or layout, and have a computer system automatically generate photo-realistic images according to that input. While classically, works that allow such automatic image content generation have followed a framework of image retrieval and composition, recent advances in deep generative models such as generative adversarial networks (GANs), variational autoencoders (VAEs), and flow-based methods have enabled more powerful and versat

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Luo, Haimin, Teng Xu, Yuheng Jiang, et al. "Artemis." ACM Transactions on Graphics 41, no. 4 (2022): 1–19. http://dx.doi.org/10.1145/3528223.3530086.

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We, humans, are entering into a virtual era and indeed want to bring animals to the virtual world as well for companion. Yet, computer-generated (CGI) furry animals are limited by tedious off-line rendering, let alone interactive motion control. In this paper, we present ARTEMIS, a novel neural modeling and rendering pipeline for generating ARTiculated neural pets with appEarance and Motion synthesIS. Our ARTEMIS enables interactive motion control, real-time animation, and photo-realistic rendering of furry animals. The core of our ARTEMIS is a neural-generated (NGI) animal engine, which adopt

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Bao, Linchao, Xiangkai Lin, Yajing Chen, et al. "High-Fidelity 3D Digital Human Head Creation from RGB-D Selfies." ACM Transactions on Graphics 41, no. 1 (2022): 1–21. http://dx.doi.org/10.1145/3472954.

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We present a fully automatic system that can produce high-fidelity, photo-realistic three-dimensional (3D) digital human heads with a consumer RGB-D selfie camera. The system only needs the user to take a short selfie RGB-D video while rotating his/her head and can produce a high-quality head reconstruction in less than 30 s. Our main contribution is a new facial geometry modeling and reflectance synthesis procedure that significantly improves the state of the art. Specifically, given the input video a two-stage frame selection procedure is first employed to select a few high-quality frames fo

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Buisine, Jérôme, André Bigand, Rémi Synave, Samuel Delepoulle, and Christophe Renaud. "Stopping Criterion during Rendering of Computer-Generated Images Based on SVD-Entropy." Entropy 23, no. 1 (2021): 75. http://dx.doi.org/10.3390/e23010075.

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The estimation of image quality and noise perception still remains an important issue in various image processing applications. It has also become a hot topic in the field of photo-realistic computer graphics where noise is inherent in the calculation process. Unlike natural-scene images, however, a reference image is not available for computer-generated images. Thus, classic methods to assess noise quantity and stopping criterion during the rendering process are not usable. This is particularly important in the case of global illumination methods based on stochastic techniques: They provide p

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Habermann, Marc, Lingjie Liu, Weipeng Xu, Gerard Pons-Moll, Michael Zollhoefer, and Christian Theobalt. "HDHumans." Proceedings of the ACM on Computer Graphics and Interactive Techniques 6, no. 3 (2023): 1–23. http://dx.doi.org/10.1145/3606927.

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Photo-real digital human avatars are of enormous importance in graphics, as they enable immersive communication over the globe, improve gaming and entertainment experiences, and can be particularly beneficial for AR and VR settings. However, current avatar generation approaches either fall short in high-fidelity novel view synthesis, generalization to novel motions, reproduction of loose clothing, or they cannot render characters at the high resolution offered by modern displays. To this end, we propose HDHumans, which is the first method for HD human character synthesis that jointly produces

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Sumit, Gunjate, Nakhate Tushar, Kshirsagar Tushar, and Sapat Yash. "Sketch to Image using GAN." International Journal of Innovative Science and Research Technology 8, no. 1 (2023): 772–77. https://doi.org/10.5281/zenodo.7588232.

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With the development of the modern age and its technologies, people are discovering ways to improve, streamline, and de-stress their lives. A difficult issue in computer vision and graphics is the creation of realistic visuals from hand-drawn sketches. There are numerous uses for the technique of creating facial sketches from real images and its inverse. Due to the differences between a photo and a sketch, photo/sketch synthesis is still a difficult problem to solve. Existing methods either require precise edge maps or rely on retrieving previously taken pictures. In order to get around the sh

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Zhao, Fuqiang, Yuheng Jiang, Kaixin Yao, et al. "Human Performance Modeling and Rendering via Neural Animated Mesh." ACM Transactions on Graphics 41, no. 6 (2022): 1–17. http://dx.doi.org/10.1145/3550454.3555451.

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We have recently seen tremendous progress in the neural advances for photo-real human modeling and rendering. However, it's still challenging to integrate them into an existing mesh-based pipeline for downstream applications. In this paper, we present a comprehensive neural approach for high-quality reconstruction, compression, and rendering of human performances from dense multi-view videos. Our core intuition is to bridge the traditional animated mesh workflow with a new class of highly efficient neural techniques. We first introduce a neural surface reconstructor for high-quality surface ge

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Dandekar, Anushree, Rohini Malladi, Payal Gore, and Dr Vipul Dalal. "Text to Image Synthesis using Generative Adversarial Networks." International Journal for Research in Applied Science and Engineering Technology 11, no. 4 (2023): 2723–30. http://dx.doi.org/10.22214/ijraset.2023.50584.

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Abstract: Image generation has been a significant field of research in computer vision and machine learning for several years. It involves generating new images that resemble real-world images based on a given input or set of inputs. This process has a wide range of applications, including video games, computer graphics, and image editing. With the advancements in deep learning, the development of generative models has revolutionized the field of image generation. Generative models such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) have demonstrated remarkable s

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Hu, Ruizhen, Xiangyu Su, Xiangkai Chen, Oliver Van Kaick, and Hui Huang. "Photo-to-shape material transfer for diverse structures." ACM Transactions on Graphics 41, no. 4 (2022): 1–14. http://dx.doi.org/10.1145/3528223.3530088.

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We introduce a method for assigning photorealistic relightable materials to 3D shapes in an automatic manner. Our method takes as input a photo exemplar of a real object and a 3D object with segmentation, and uses the exemplar to guide the assignment of materials to the parts of the shape, so that the appearance of the resulting shape is as similar as possible to the exemplar. To accomplish this goal, our method combines an image translation neural network with a material assignment neural network. The image translation network translates the color from the exemplar to a projection of the 3D s

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Verhoeven, G. J. "COMPUTER GRAPHICS MEETS IMAGE FUSION: THE POWER OF TEXTURE BAKING TO SIMULTANEOUSLY VISUALISE 3D SURFACE FEATURES AND COLOUR." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-2/W2 (August 17, 2017): 295–302. http://dx.doi.org/10.5194/isprs-annals-iv-2-w2-295-2017.

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Since a few years, structure-from-motion and multi-view stereo pipelines have become omnipresent in the cultural heritage domain. The fact that such Image-Based Modelling (IBM) approaches are capable of providing a photo-realistic texture along the threedimensional (3D) digital surface geometry is often considered a unique selling point, certainly for those cases that aim for a visually pleasing result. However, this texture can very often also obscure the underlying geometrical details of the surface, making it very hard to assess the morphological features of the digitised artefact or scene.

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Zhong, Fangcheng, Akshay Jindal, Ali Özgür Yöntem, Param Hanji, Simon J. Watt, and Rafał K. Mantiuk. "Reproducing reality with a high-dynamic-range multi-focal stereo display." ACM Transactions on Graphics 40, no. 6 (2021): 1–14. http://dx.doi.org/10.1145/3478513.3480513.

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With well-established methods for producing photo-realistic results, the next big challenge of graphics and display technologies is to achieve perceptual realism --- producing imagery indistinguishable from real-world 3D scenes. To deliver all necessary visual cues for perceptual realism, we built a High-Dynamic-Range Multi-Focal Stereo Display that achieves high resolution, accurate color, a wide dynamic range, and most depth cues, including binocular presentation and a range of focal depth. The display and associated imaging system have been designed to capture and reproduce a small near-eye

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Gao, Lin, Feng-Lin Liu, Shu-Yu Chen, et al. "SketchFaceNeRF: Sketch-based Facial Generation and Editing in Neural Radiance Fields." ACM Transactions on Graphics 42, no. 4 (2023): 1–17. http://dx.doi.org/10.1145/3592100.

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Realistic 3D facial generation based on Neural Radiance Fields (NeRFs) from 2D sketches benefits various applications. Despite the high realism of free-view rendering results of NeRFs, it is tedious and difficult for artists to achieve detailed 3D control and manipulation. Meanwhile, due to its conciseness and expressiveness, sketching has been widely used for 2D facial image generation and editing. Applying sketching to NeRFs is challenging due to the inherent uncertainty for 3D generation with 2D constraints, a significant gap in content richness when generating faces from sparse sketches, a

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Zheng, Zerong, Xiaochen Zhao, Hongwen Zhang, Boning Liu, and Yebin Liu. "AvatarReX: Real-time Expressive Full-body Avatars." ACM Transactions on Graphics 42, no. 4 (2023): 1–19. http://dx.doi.org/10.1145/3592101.

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We present AvatarReX, a new method for learning NeRF-based full-body avatars from video data. The learnt avatar not only provides expressive control of the body, hands and the face together, but also supports real-time animation and rendering. To this end, we propose a compositional avatar representation, where the body, hands and the face are separately modeled in a way that the structural prior from parametric mesh templates is properly utilized without compromising representation flexibility. Furthermore, we disentangle the geometry and appearance for each part. With these technical designs

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Zhu, Shilin, Zexiang Xu, Tiancheng Sun, et al. "Photon-Driven Neural Reconstruction for Path Guiding." ACM Transactions on Graphics 41, no. 1 (2022): 1–15. http://dx.doi.org/10.1145/3476828.

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Although Monte Carlo path tracing is a simple and effective algorithm to synthesize photo-realistic images, it is often very slow to converge to noise-free results when involving complex global illumination. One of the most successful variance-reduction techniques is path guiding, which can learn better distributions for importance sampling to reduce pixel noise. However, previous methods require a large number of path samples to achieve reliable path guiding. We present a novel neural path guiding approach that can reconstruct high-quality sampling distributions for path guiding from a sparse

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Liu, Lingjie, Marc Habermann, Viktor Rudnev, Kripasindhu Sarkar, Jiatao Gu, and Christian Theobalt. "Neural actor." ACM Transactions on Graphics 40, no. 6 (2021): 1–16. http://dx.doi.org/10.1145/3478513.3480528.

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We propose Neural Actor (NA), a new method for high-quality synthesis of humans from arbitrary viewpoints and under arbitrary controllable poses. Our method is developed upon recent neural scene representation and rendering works which learn representations of geometry and appearance from only 2D images. While existing works demonstrated compelling rendering of static scenes and playback of dynamic scenes, photo-realistic reconstruction and rendering of humans with neural implicit methods, in particular under user-controlled novel poses, is still difficult. To address this problem, we utilize

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Santos, Pedro, Martin Ritz, Constanze Fuhrmann, and Dieter Fellner. "3D mass digitization: a milestone for archeological documentation." Virtual Archaeology Review 8, no. 16 (2017): 1. http://dx.doi.org/10.4995/var.2017.6321.

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In the heritage field, the demand for fast and efficient 3D digitization technologies for historic remains is increasing. Besides, 3D digitization has proved to be a promising approach to enable precise reconstructions of objects. Yet, unlike the digital acquisition of cultural goods in 2D widely used today, 3D digitization often still requires a significant investment of time and money. To make it more widely available to heritage institutions, the <em>Competence Center for Cultural Heritage Digitization</em> at the <em>Fraunhofer Institute for Computer Graphics Research IGD

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Dong, Deng Yu. "Accelerating Neural Radiance Field by network pruning." Applied and Computational Engineering 45, no. 1 (2024): 152–67. http://dx.doi.org/10.54254/2755-2721/45/20241047.

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Novel view synthesis, a crucial problem in computer graphics with extensive applications, has gained significant attention due to its increasing demand in fields such as autonomous driving, virtual reality, film, and the visual arts. Recent advancements in machine learning have led to progress in generating photo-realistic imagery, particularly with the Neural Radiance Fields (NeRF) method. Despite its impressive results, NeRF requires high computational resources for training and synthesis, impeding its real-world applications. This work aims to investigate the potential of network pruning to

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Baraheem, Samah S., and Tam V. Nguyen. "AI vs. AI: Can AI Detect AI-Generated Images?" Journal of Imaging 9, no. 10 (2023): 199. http://dx.doi.org/10.3390/jimaging9100199.

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The proliferation of Artificial Intelligence (AI) models such as Generative Adversarial Networks (GANs) has shown impressive success in image synthesis. Artificial GAN-based synthesized images have been widely spread over the Internet with the advancement in generating naturalistic and photo-realistic images. This might have the ability to improve content and media; however, it also constitutes a threat with regard to legitimacy, authenticity, and security. Moreover, implementing an automated system that is able to detect and recognize GAN-generated images is significant for image synthesis mo

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Storozhuk, S. S., and M. H. Lysachenko. "MODERN ARCHITECTURAL SOFTWARE AND ITS DEVELOPMENT PROSPECTS. «PIPELINE»." Regional problems of architecture and urban planning, no. 16 (December 23, 2022): 220–26. http://dx.doi.org/10.31650/2707-403x-2022-16-220-226.

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The article examines the methodology of programs used by architects and other specialists in creative specialties. The transition to remote work has changed the standards of teaching and working material in Higher Education Institutions and forced most of society to use modern computer technologies. The main problem of the software is its constant updating, which leads to the difficulty of self-study, regardless of the availability of a huge amount of information on Internet resources. Moreover, depending on the specialization of the profession, as well as personal interests, at least three or

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Stoll, Stephanie, Necati Cihan Camgoz, Simon Hadfield, and Richard Bowden. "Text2Sign: Towards Sign Language Production Using Neural Machine Translation and Generative Adversarial Networks." International Journal of Computer Vision 128, no. 4 (2020): 891–908. http://dx.doi.org/10.1007/s11263-019-01281-2.

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AbstractWe present a novel approach to automatic Sign Language Production using recent developments in Neural Machine Translation (NMT), Generative Adversarial Networks, and motion generation. Our system is capable of producing sign videos from spoken language sentences. Contrary to current approaches that are dependent on heavily annotated data, our approach requires minimal gloss and skeletal level annotations for training. We achieve this by breaking down the task into dedicated sub-processes. We first translate spoken language sentences into sign pose sequences by combining an NMT network

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Ciampi, Luca, Nicola Messina, Fabrizio Falchi, Claudio Gennaro, and Giuseppe Amato. "Virtual to Real Adaptation of Pedestrian Detectors." Sensors 20, no. 18 (2020): 5250. http://dx.doi.org/10.3390/s20185250.

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Pedestrian detection through Computer Vision is a building block for a multitude of applications. Recently, there has been an increasing interest in convolutional neural network-based architectures to execute such a task. One of these supervised networks’ critical goals is to generalize the knowledge learned during the training phase to new scenarios with different characteristics. A suitably labeled dataset is essential to achieve this purpose. The main problem is that manually annotating a dataset usually requires a lot of human effort, and it is costly. To this end, we introduce ViPeD (Virt

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Liu, Xiyao, Yang Liu, Yuhao Zheng, et al. "Semantics‐guided generative diffusion model with a 3DMM model condition for face swapping." Computer Graphics Forum, October 30, 2023. http://dx.doi.org/10.1111/cgf.14949.

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AbstractFace swapping is a technique that replaces a face in a target media with another face of a different identity from a source face image. Currently, research on the effective utilisation of prior knowledge and semantic guidance for photo‐realistic face swapping remains limited, despite the impressive synthesis quality achieved by recent generative models. In this paper, we propose a novel conditional Denoising Diffusion Probabilistic Model (DDPM) enforced by a two‐level face prior guidance. Specifically, it includes (i) an image‐level condition generated by a 3D Morphable Model (3DMM), a

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Cheng, Yuhao, Yichao Yan, Wenhan Zhu, Ye Pan, Bowen Pan, and Xiaokang Yang. "Head3D: Complete 3D Head Generation via Tri-plane Feature Distillation." ACM Transactions on Multimedia Computing, Communications, and Applications, January 25, 2024. http://dx.doi.org/10.1145/3635717.

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Head generation with diverse identities is an important task in computer vision and computer graphics, widely used in multimedia applications. However, current full-head generation methods require a large number of 3D scans or multi-view images to train the model, resulting in expensive data acquisition costs. To address this issue, we propose Head3D, a method to generate full 3D heads with limited multi-view images. Specifically, our approach first extracts facial priors represented by tri-planes learned in EG3D, a 3D-aware generative model, and then proposes feature distillation to deliver t

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Kim, S. M., C. Choi, H. Heo, and Y. M. Kim. "Robust Novel View Synthesis with Color Transform Module." Computer Graphics Forum, October 30, 2023. http://dx.doi.org/10.1111/cgf.14931.

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AbstractThe advancements of the Neural Radiance Field (NeRF) and its variants have demonstrated remarkable capabilities in generating photo‐realistic novel views from a small set of input images. While recent works suggest various techniques and model architectures that enhance speed or reconstruction quality, little attention is paid to exploring the RGB color space of input images. In this paper, we propose a universal color transform module that can maximally harness the captured evidence for the neural networks at hand. The color transform module utilizes an encoder‐decoder framework that

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Liang, Chao, Qinghua Wang, Yunlin Chen, and Minjie Tang. "Wav2Lip‐HR: Synthesising clear high‐resolution talking head in the wild." Computer Animation and Virtual Worlds, December 15, 2023. http://dx.doi.org/10.1002/cav.2226.

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AbstractTalking head generation aims to synthesize a photo‐realistic speaking video with accurate lip motion. While this field has attracted more attention in recent audio‐visual researches, most existing methods do not achieve the simultaneous improvement of lip synchronization and visual quality. In this paper, we propose Wav2Lip‐HR, a neural‐based audio‐driven high‐resolution talking head generation method. With our technique, all required to generate a clear high‐resolution lip sync talking video is an image/video of the target face and an audio clip of any speech. The primary benefit of o

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Rossoni, Marco, Matteo Pozzi, Giorgio Colombo, Marco Gribaudo, and Pietro Piazzolla. "Physically-based Rendering of Animated Point Clouds for eXtended Reality." Journal of Computing and Information Science in Engineering, September 28, 2023, 1–9. http://dx.doi.org/10.1115/1.4063559.

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Abstract Point cloud 3D models are becoming more and more popular thanks to the spreading of scanning systems employed in many fields. When used for rendering purposes, point clouds are usually displayed with their original color acquired at scan time, without considering the lighting condition of the scene where the model is placed. This leads to a lack of realism in many contexts, especially in the case of animated point clouds employed in eXtended Reality applications where it would be desirable to have the model reacting to incoming light and integrating with the surrounding environment. T

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Tovanche-Picon, Hector, Javier González-Trejo, Ángel Flores-Abad, Miguel Ángel García-Terán, and Diego Mercado-Ravell. "Real-time safe validation of autonomous landing in populated areas: from virtual environments to Robot-In-The-Loop." Virtual Reality 28, no. 1 (2024). http://dx.doi.org/10.1007/s10055-024-00965-6.

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AbstractSafe autonomous landing for Unmanned Aerial Vehicles (UAVs) in populated areas is a crucial aspect for successful integration of UAVs in populated environments. Nonetheless, validating autonomous landing in real scenarios is a challenging task with a high risk of injuring people. In this work, we propose a framework for safe real-time and thorough evaluation of vision-based autonomous landing in populated scenarios, using photo-realistic virtual environments and physics-based simulation. The proposed evaluation pipeline includes the use of Unreal graphics engine coupled with AirSim for

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Manyar, Omey Mohan, Junyan Cheng, Reuben Levine, Vihan Krishnan, Jernej Barbic, and Satyandra K. Gupta. "PHYSICS INFORMED SYNTHETIC IMAGE GENERATION FOR DEEP LEARNING BASED DETECTION OF WRINKLES AND FOLDS." Journal of Computing and Information Science in Engineering, November 22, 2022, 1–18. http://dx.doi.org/10.1115/1.4056295.

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Abstract Deep learning based image segmentation methods have showcased tremendous potential in defect detection applications for several manufacturing processes. Currently, majority of deep learning research for defect detection focuses on manufacturing processes where the defects have well defined features and there is tremendous amount of image data available to learn such a data dense model. This makes deep learning unsuitable for defect detection in high-mix low volume manufacturing applications where data is scarce and the features of defects are not well defined due to the nature of the

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Park, Byung-Seo, Woosuk Kim, Jin-Kyum Kim, Dong-Wook Kim, and Young-Ho Seo. "Quality Enhancement of 3D Volumetric Contents Based on 6DoF for 5G Telepresence Service." Journal of Web Engineering, March 22, 2022. http://dx.doi.org/10.13052/jwe1540-9589.2138.

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In general, the importance of 6DoF (degree of freedom) 3D (dimension) volumetric contents technology is emerging in 5G (generation) telepresence service, Web-based (WebGL) graphics, computer vision, robotics, and next-generation augmented reality. Since it is possible to acquire RGB images and depth images in real-time through depth sensors that use various depth acquisition methods such as time of flight (ToF) and lidar, many changes have been made in object detection, tracking, and recognition research. In this paper, we propose a method to improve the quality of 3D models for 5G telepresenc

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Cheng, Mengjia, Yu Zhuang, Hanjiang Zhao, Meng Li, Lingfeng Fan, and Hongbo Yu. "Development of a maxillofacial virtual surgical system based on biomechanical parameters of facial soft tissue." International Journal of Computer Assisted Radiology and Surgery, May 15, 2022. http://dx.doi.org/10.1007/s11548-022-02657-5.

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Abstract Purpose Lack of biomechanical force model of soft tissue hinders the development of virtual surgical simulation in maxillofacial surgery. In this study, a physical model of facial soft tissue based on real biomechanical parameters was constructed, and a haptics-enabled virtual surgical system was developed to simulate incision-making process on facial soft tissue and to help maxillofacial surgery training. Methods CT data of a 25-year-old female patient were imported into Mimics software to reconstruct 3D models of maxillofacial soft and skeletal tissues. 3dMD stereo-photo of the pati

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Brennan, Joseph. "Slash Manips: Remixing Popular Media with Gay Pornography." M/C Journal 16, no. 4 (2013). http://dx.doi.org/10.5204/mcj.677.

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A slash manip is a photo remix that montages visual signs from popular media with those from gay pornography, creating a new cultural artefact. Slash (see Russ) is a fannish practice that homoeroticises the bonds between male media characters and personalities—female pairings are categorised separately as ‘femslash’. Slash has been defined almost exclusively as a female practice. While fandom is indeed “women-centred” (Bury 2), such definitions have a tendency to exclude male contributions. Remix has been well acknowledged in discussions on slash, most notably video remix in relation to slash

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