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Vehicle Pose Measurement with a Single Image via the Double-Dual-Ellipse Feature of Wheel Rims. [PDF]
Sensors (Basel)Xu G, Wang R, Lin H.
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BBDM: Image-to-Image Translation With Brownian Bridge Diffusion Models [PDF]
, 2023 Image-to-image translation is an important and challenging problem in computer vision and image processing. Diffusion models (DM) have shown great potentials for high-quality image synthesis, and have gained competitive performance on the task of image ...
Yukun Lai, Kaitao Xue
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Multimodal Unsupervised Image-to-Image Translation [PDF]
Lecture Notes in Computer Science, 2018 Unsupervised image-to-image translation is an important and challenging problem in computer vision. Given an image in the source domain, the goal is to learn the conditional distribution of corresponding images in the target domain, without seeing any pairs of corresponding images.
Serge Belongie, Ming-Yu Liu, Jan Kautz
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Deep Generative Adversarial Networks for Image-to-Image Translation: A Review
Symmetry, 2020 Many image processing, computer graphics, and computer vision problems can be treated as image-to-image translation tasks. Such translation entails learning to map one visual representation of a given input to another representation.
Aziz Alotaibi
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Memorability based image to image translation
Twelfth International Conference on Machine Vision (ICMV 2019), 2020This paper presents a memorability based image-to-image translation technique to make an image more memorable while retaining its high-level contents. Conventionally, the image-to-image translation task aims to learn the mapping between images of two different domains using a set of aligned image pairs.
Sathisha Basavaraju +2 more
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Domain Adaptive Image-to-Image Translation
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020Unpaired image-to-image translation (I2I) has achieved great success in various applications. However, its generalization capacity is still an open question. In this paper, we show that existing I2I models do not generalize well for samples outside the training domain. The cause is twofold. First, an I2I model may not work well when testing samples are
Ying-Cong Chen +2 more
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Deep Learning Image-To-Image Translation For Animation
2021 IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW), 2021This paper presents a novel application for animation of cartoon characters. The system consists of two components: (a) a generative adversarial network that is trained to generate comic characters from edge images, and (b) an edge detector that takes input from portraits and then generates comic characters based on the resulting edge images.
Carolina Rutili de Lima, Jacky Baltes
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Edge Sensitive Unsupervised Image-to-Image Translation
2020 28th Signal Processing and Communications Applications Conference (SIU), 2020The goal of unsupervised image-to-image translation (IIT) is to learn a mapping from the source domain to the target domain without using paired image sets. Most of the current IIT methods apply adversarial training to match the distribution of the translated images to the distribution of the target images. However, this may create artifacts in uniform
Ibrahim Batuhan Akkaya, Ugur Halici
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Generative image completion with image-to-image translation
Neural Computing and Applications, 2019Though many methods have been proposed, image completion still remains challenge; besides textured patterns completion, it often requires high-level understanding of scenes and objects being completed. More recently, deep convolutional generative adversarial networks have been turned into an efficient tool for image completion.
Shuzhen Xu, Qing Zhu 0004, Jin Wang 0023
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