for generating a high-resolution image, and if the time of period of shutter-on is reduced and the time of period of shutter-off is increased, the time deviation is made conspicuous, and when an irradiation amount of a subject image is extremely small, a practical image cannot be obtained...
[CVPR2018笔记]High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs CVPR 2018 ORAL 本文解决了GAN生成高分辨率突破的问题,分辨率达到了2048*1024,方法精细,值得深入来看。 先来看generator: 如图言,中间部分的G1在低分辨率情况下训练,然后在前后又分别加上G2,注意左边部分的G2的输出和G1...
we seek to explore using pure transformers to build a generative adversarial network for high-resolution image synthesis. To this end, we believe that local attention is crucial to strike the balance between computational efficiency and modeling capacity. Hence, the proposed generator adopts Swin trans...
Snap Inc.'s research team recently launched an AI image generator named SnapGen, capable of generating high-resolution images directly on high-end smartphones. This technology allows users to enjoy an efficient and convenient image creation experience on their phones, breaking the limitations of trad...
Despite the tantalizing success in a broad of vision tasks, transformers have not yet demonstrated on-par ability as ConvNets in high-resolution image generative modeling. In this paper, we seek to explore using pure transformers to build a generative adversarial network for high-resolution image ...
[VQ-GAN](Taming Transformers for High-Resolution Image Synthesis) 时间:CVPR2021 oral 21.06 机构:Heidelberg Collaboratory for Image Processing, IWR, Heidelberg University, Germany TL;DR Transformer优势在于能较好地长距离建模sequence数据,而CNN优势是天生对局部位置关系具有归纳偏差。本文结合两者特征,利用CNN建立...
Generator以低分辨率图像为输入并填充孔洞。同时,注意力得分由生成器的注意力计算模块(ACM,Attention Computing Model)计算。此外,上下文残差是通过从原始输入中减去大的模糊图像来计算的,然后通过注意力转移模块(ATM)根据上下文残差和注意力得分计算掩码区域中的聚合残差(第3.2.2节)。最后,将聚合残差与上采样的修复结果...
Hence, employing GANs enables the generation of high-resolution, realistic images that support object manipulation and diverse outcomes from a single input. This method not only enhances image synthesis techniques but also unlocks numerous applications in urban planning and design. 展开 ...
Conditional GANs have enabled a variety of applications, but the results are often limited to low-resolution and still far from realistic. In this work, we generate 2048x1024 visually appealing results with a novel adversarial loss, as well as new multi-scale generator and discriminator ...
Deep neural networks have been successfully applied to problems such as image segmentation, image super-resolution, coloration and image inpainting. In this work we propose the use of convolutional neural networks (CNN) for image inpainting of large regions in high-resolution textures. Due to limited...