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A survey of the state-of-the-art in patch-based synthesis

Computational Visual Media 2017年第1期3卷 3-20页

作者： connelly barnes Fang-Lue Zhang University of Virginia TNList Tsinghua University

This paper surveys the state-of-the-art of research in patch-based synthesis. Patch-based methods synthesize output images by copying small regions from exemplar imagery. This line of research originated from an area called "texture synthesis", which focused on creating regular or semi-regular textures from small exemplars. However, more recently, much research has focused on synthesis of larger and more diverse imagery, such as photos, photo collections, videos, and light fields. Additionally, recent research has focused on customizing the synthesis process for particular problem domains, such as synthesizing artistic or decorative brushes, synthesis of rich materials, and synthesis for 3D fabrication. This report investigates recent papers that follow these themes, with a particular emphasis on papers published since 2009,when the last survey in this area was published. This survey can serve as a tutorial for readers who are not yet familiar with these topics, as well as provide comparisons between these papers, and highlight some open problems in this area.

关键词： texture patch image synthesis texture synthesis

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Coherent video generation for multiple hand-held cameras with dynamic foreground

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Computational Visual Media 2020年第3期6卷 291-306页

作者： Fang-Lue Zhang connelly barnes Hao-Tian Zhang Junhong Zhao Gabriel Salas Victoria University of Wellington Wellington 6012New Zealand Adobe Research SeattleUSA Stanford University San FranciscoUSA

For many social events such as public performances, multiple hand-held cameras may capture the same event. This footage is often collected by amateur cinematographers who typically have little control over the scene and may not pay close attention to the camera. For these reasons, each individually captured video may fail to cover the whole time of the event, or may lose track of interesting foreground content such as a performer. We introduce a new algorithm that can synthesize a single smooth video sequence of moving foreground objects captured by multiple hand-held cameras. This allows later viewers to gain a cohesive narrative experience that can transition between different cameras, even though the input footage may be less than ideal. We first introduce a graph-based method for selecting a good transition route. This allows us to automatically select good cut points for the hand-held videos, so that smooth transitions can be created between the resulting video shots. We also propose a method to synthesize a smooth photorealistic transition video between each pair of hand-held cameras, which preserves dynamic foreground content during this transition. Our experiments demonstrate that our method outperforms previous state-of-the-art methods, which struggle to preserve dynamic foreground content.

关键词： dynamic preserve camera

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Preface

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Journal of Computer Science & Technology 2021年第3期36卷 463-464页

作者： Hu Shi-Min barnes connelly Tu Chang-He Department of Computer Science and Technology Tsinghua University Beijing China Adobe Research Seattle USA School of Computer Science and Technology Shandong University Qingdao China

The Computational Visual Media(CVM)conference series is intended to provide a major international forum for exchanging novel research ideas and significant computational methods that either underpin or apply visual *** primary goal is to promote cross-disciplinary research to amalgamate aspects of computer graphics,computer vision,machine learning,image and video processing,visualization and geometric *** main topics of interest to CVM include classification,composition,retrieval,synthesis,cognition and understanding of visual media(e.g.,images,video,3D geometry).

关键词： computer graphics visual

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