A Survey of Computer Graphics Facial Animation Methods: Comparing Traditional Approaches to Machine Learning Methods

Human communications rely on facial expression to denote mood, sentiment, and intent. Realistic facial animation of computer graphic models of human faces can be difficult to achieve as a result of the many details that must be approximated in generating believable facial expressions. Many theoretical approaches have been researched and implemented to create more and more accurate animations that can effectively portray human emotions. Even though many of these approaches are able to generate realistic looking expressions, they typically require a lot of artistic intervention to achieve a believable result. To reduce the intervention needed to create realistic facial animation, new approaches that utilize machine learning are being researched to reduce the amount of effort needed to generate believable facial animations. This survey paper summarizes over 20 research papers related to facial animation and compares the traditional animation approaches to newer machine learning methods as well as highlights the strengths, weaknesses, and use cases of each different approach

Higher level techniques for the artistic rendering of images and video

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Freeform User Interfaces for Graphical Computing

報告番号: 甲15222 ; 学位授与年月日: 2000-03-29 ; 学位の種別: 課程博士 ; 学位の種類: 博士(工学) ; 学位記番号: 博工第4717号 ; 研究科・専攻: 工学系研究科情報工学専

A shader based approach to painterly rendering

The purpose of this thesis is to develop a texture-based painterly shader that would render computer generated objects or scenes with strokes that are visually similar to paint media like watercolor, oil paint or dry media such as crayons, chalk, et cetera. This method would need an input scene in the form of three dimensional polygonal or NURBS meshes. While the structure of the meshes and the lighting in the scene would both play a crucial role in the final appearance of the scene, the painterly look will be imparted through a shader. This method, therefore, is essentially a rendering technique. Several modifiable parameters in the shader gives the user artistic freedom while overall introducing some amount of automation in the painterly rendering process

Towards photo watercolorization with artistic verisimilitude

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Deep Learning for Free-Hand Sketch: A Survey

Free-hand sketches are highly illustrative, and have been widely used by humans to depict objects or stories from ancient times to the present. The recent prevalence of touchscreen devices has made sketch creation a much easier task than ever and consequently made sketch-oriented applications increasingly popular. The progress of deep learning has immensely benefited free-hand sketch research and applications. This paper presents a comprehensive survey of the deep learning techniques oriented at free-hand sketch data, and the applications that they enable. The main contents of this survey include: (i) A discussion of the intrinsic traits and unique challenges of free-hand sketch, to highlight the essential differences between sketch data and other data modalities, e.g., natural photos. (ii) A review of the developments of free-hand sketch research in the deep learning era, by surveying existing datasets, research topics, and the state-of-the-art methods through a detailed taxonomy and experimental evaluation. (iii) Promotion of future work via a discussion of bottlenecks, open problems, and potential research directions for the community.Comment: This paper is accepted by IEEE TPAM