sketch 相关论文

sketch 相关论文

  1. Sketch Simplification

    We present a novel technique to simplify sketch drawings based on learning a series of convolution operators. In contrast to existing approaches that require vector images as input, we allow the more general and challenging input of rough raster sketches such as those obtained from scanning pencil sketches. We convert the rough sketch into a simplified version which is then amendable for vectorization. This is all done in a fully automatic way without user intervention. Our model consists of a fully convolutional neural network which, unlike most existing convolutional neural networks, is able to process images of any dimensions and aspect ratio as input, and outputs a simplified sketch which has the same dimensions as the input image. In order to teach our model to simplify, we present a new dataset of pairs of rough and simplified sketch drawings. By leveraging convolution operators in combination with efficient use of our proposed dataset, we are able to train our sketch simplification model. Our approach naturally overcomes the limitations of existing methods, e.g., vector images as input and long computation time; and we show that meaningful simplifications can be obtained for many different test cases. Finally, we validate our results with a user study in which we greatly outperform similar approaches and establish the state of the art in sketch simplification of raster images.

  2. Sketch-Based Image Synthesis

    When the input to pix2pix translation [9] is a badly drawn sketch, the output follows the input edges due to the strict alignment imposed by the translation process. In this paper we propose sketch-to-image generation, where the output edges do not necessarily follow the input edges. We

    address the image generation problem using a novel joint image completion approach, where the sketch provides the image context for completing, or generating the output image.We train a deep generative model to learn the joint distribution of sketch and the corresponding image by using joint images. Our deep contextual completion approach has several advantages. First, the simple joint image representation allows for simple and effective definition of losses in the same joint image-sketch space, which avoids complicated issues in cross-domain learning. Second, while the output is related to its input overall, the generated features exhibit more freedom in appearance and do not strictly align with the input features. Third, from the joint image’s point of view, image and sketch are of no difference, thus exactly the same deep joint image completion network can be used for image-to-sketch generation. Experiments evaluated on three different datasets show that the proposed approach can generate more realistic images than the state-ofthe-arts on challenging inputs and generalize well on common categories.

  3. Sketch-Based Image Synthesis

    Recently, there have been several promising methods to generate realistic imagery from deep convolutional networks. These methods sidestep the traditional computer graphics rendering pipeline and instead generate imagery at the pixel level by learning from large collections of photos (e.g. faces or bedrooms). However, these methods are of limited utility because it is difficult for a user to control what the network produces. In this paper, we propose a deep adversarial image synthesis architecture that is conditioned on sketched boundaries and sparse color strokes to generate realistic cars, bedrooms, or faces. We demonstrate a sketch based image synthesis system which allows users to scribble over the sketch to indicate preferred color for objects. Our network can then generate convincing images that satisfy both the color and the sketch constraints of user. The network is feed-forward which allows users to see the effect of their edits in real time. We compare to recent work on sketch to image synthesis and show that our approach can generate more realistic, more diverse, and more controllable outputs. The architecture is also effective at user-guided colorization of grayscale images.

原文地址:https://www.cnblogs.com/xiconxi/p/8366028.html

时间: 2024-10-04 06:27:57

sketch 相关论文的相关文章

Kintinuous 相关论文 Volume Fusion 详解

近几个月研读了不少RGBD-SLAM的相关论文,Whelan的Volume Fusion系列文章的效果确实不错,而且开源代码Kintinuous结构清晰,易于编译和运行,故把一些学习时自己的理解和经验写出来,供大家参考,同时希望各位批评指正. 研读之前已经发现有中文博客做了一些解析,我也受益不少.参见fuxingyin的blog:Kintinuous 解析 .不过有些地方已经不够详细,故此文重新进行解读.可能某些地方会重复. 本文是在自己阅读.整理.代码实践的基础上做的一些结果,希望对相关研究者

复杂性研究相关论文

                复杂性研究,旨在理解那些由彼此相互作用的微小元素所组成的系统的行为和性质,         此类研究往往需要依靠各学派各领域的专业知识以及跨学科合作.                 作为跨学科研究的理想期刊,Nature Communications收录的论文覆盖了包括物理学.         生命科学在内的广泛主题. 生态与演化一栏,罗列了探索基因.个体及社区网络动态的文章,这些研究多采用经验数据及数学演算. 网络医疗一栏,涉及到生物学中的计算机建模研究,包括

MR 图像分割 相关论文摘要整理

<多分辨率水平集算法的乳腺MR图像分割> 针对乳腺 MR 图像信息量大.灰度不均匀.边界模糊.难分割的特点, 提出一种多分辨率水平集乳腺 MR图像分割算法. 算法的核心是首先利用小波多尺度分解对图像进行多尺度空间分析, 得到粗尺度图像; 然后对粗尺度图像利用改进 CV 模型进行分割. 为了去除乳腺 MR 图像中灰度偏移场对分割效果的影响, 算法中引入局部拟合项, 并用核函数进一步改进 CV模型, 进而对粗尺度分割效果进行优化处理. 仿真和临床数据分割结果表明, 所提算法分割灰度不均匀图像具有较

智慧工厂相关论文

1 An Integrated Industrial Ethernet Solution for the Implementation of Smart Factory 在本文中,我们的目标是为智能工厂提供一个网络解决方案.我们的动机是建立一个平面网络拓扑,同时满足不同参与者和层在带宽.可靠性.实时处理.安全性和语义方面的异构需求. 2 A Big Data Analytics Platform for Smart Factories in Small and Medium-Sized Manu

线性扫描寄存器分配算法--相关论文

http://cs.au.dk/~mis/dOvs/slides/Kevin-linear-scan-reg-alloc.pdf ftp://ftp.ssw.uni-linz.ac.at/pub/Papers/Moe02.PDF Greedy Register Allocation in LLVM 3.0 http://blog.llvm.org/2011/09/greedy-register-allocation-in-llvm-30.html http://lists.cs.uiuc.edu

云数据库研究 相关论文阅读

<云数据库研究> 厦门大学 林子雨 一堆大牛逼.

ICCV2013、CVPR2013、ECCV2013目标检测相关论文

CVPapers 网址: http://www.cvpapers.com/   ICCV2013 Papers about Object Detection: 1. Regionlets for Generic Object Detection. Xiaoyu Wang, Ming Yang, Shenghuo Zhu, Yuanqing Lin .(暂无源码提供) Website: http://www.xiaoyumu.com/project/detection 这篇文章提出了一种新的特征描

DQN 相关论文。

开山之作: <Playing Atari with Deep Reinforcement Learning>(NIPS) http://export.arxiv.org/pdf/1312.5602 <Human-level control through deep reinforcementlearnin> https://www.cs.swarthmore.edu/~meeden/cs63/s15/nature15b.pdf 使用2个网络,减少了相关性,每隔一定时间,替换参数.

暑假CV-QKD的相关论文单词集(第一弹)

CV-QKD  连续变量-量子秘钥分发 Quadrature  正交 Photon     光子 Coherent    连续的,连贯的 Reconciliation   调解 Cryptography   密码学 Eavesdropper   窃听者,就是三个人中的EVE. Homodyne detection 零差检测 Heterodyne detection 外差检测 Reverse reconciliation 反向协调 In the case of  在...的条件下 Modified