Results 11 to 20 of about 98,087,126 (282)
Mechanisms of Generative Image-to-Image Translation Networks [PDF]
IEEE AccessExisting image-to-image translation models often rely on complex architectures with multiple loss terms, making them difficult to interpret and computationally expensive.
Guangzong Chen +4 more
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All-in-one medical image-to-image translation [PDF]
Cell Reports: MethodsSummary: The growing availability of public multi-domain medical image datasets enables training omnipotent image-to-image (I2I) translation models. However, integrating diverse protocols poses challenges in domain encoding and scalability. Therefore, we
Luyi Han +12 more
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GD-StarGAN: Multi-domain image-to-image translation in garment design. [PDF]
PLoS ONE, 2020 In the field of fashion design, designing garment image according to texture is actually changing the shape of texture image, and image-to-image translation based on Generative Adversarial Network (GAN) can do this well.
Yangyun Shen, Runnan Huang, Wenkai Huang
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Panoramic Image-to-Image Translation [PDF]
CoRR, 2023 In this paper, we tackle the challenging task of Panoramic Image-to-Image translation (Pano-I2I) for the first time. This task is difficult due to the geometric distortion of panoramic images and the lack of a panoramic image dataset with diverse conditions, like weather or time.
Soohyun Kim +6 more
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Hypercomplex Image- to- Image Translation [PDF]
2022 International Joint Conference on Neural Networks (IJCNN), 2022 Image-to-image translation (I2I) aims at transferring the content representation from an input domain to an output one, bouncing along different target domains. Recent I2I generative models, which gain outstanding results in this task, comprise a set of diverse deep networks each with tens of million parameters.
Eleonora Grassucci +3 more
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Vector Quantized Image-to-Image Translation
, 2022 Current image-to-image translation methods formulate the task with conditional generation models, leading to learning only the recolorization or regional changes as being constrained by the rich structural information provided by the conditional contexts.
Yu-Jie Chen +4 more
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Towards Instance-Level Image-To-Image Translation [PDF]
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019 Unpaired Image-to-image Translation is a new rising and challenging vision problem that aims to learn a mapping between unaligned image pairs in diverse domains. Recent advances in this field like MUNIT and DRIT mainly focus on disentangling content and style/attribute from a given image first, then directly adopting the global style to guide the model
Zhiqiang Shen +4 more
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StyleFlow For Content-Fixed Image to Image Translation [PDF]
CoRR, 2022 Image-to-image (I2I) translation is a challenging topic in computer vision. We divide this problem into three tasks: strongly constrained translation, normally constrained translation, and weakly constrained translation. The constraint here indicates the extent to which the content or semantic information in the original image is preserved.
Weichen Fan +4 more
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Is image-to-image translation the panacea for multimodal image registration? A comparative study [PDF]
PLoS ONE, 2022 Despite current advancement in the field of biomedical image processing, propelled by the deep learning revolution, multimodal image registration, due to its several challenges, is still often performed manually by specialists.
Jiahao Lu +3 more
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Metalens-style image synthesis for metalens imaging via image-to-image translation [PDF]
Scientific ReportsMetalenses offer wafer-scale, ultra-thin optics for compact cameras, but strong chromatic and field-dependent aberrations still limit their practical use.
Chanik Kang +4 more
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