Zobrazeno 1 - 10
of 141
pro vyhledávání: '"Omachi, Shinichiro"'
Layout generation is a task to synthesize a harmonious layout with elements characterized by attributes such as category, position, and size. Human designers experiment with the placement and modification of elements to create aesthetic layouts, howe
Externí odkaz:
http://arxiv.org/abs/2409.16689
Autor:
Lampe, Ajda, Stopar, Julija, Jain, Deepak Kumar, Omachi, Shinichiro, Peer, Peter, Štruc, Vitomir
Recent developments in deep generative models have opened up a wide range of opportunities for image synthesis, leading to significant changes in various creative fields, including the fashion industry. While numerous methods have been proposed to be
Externí odkaz:
http://arxiv.org/abs/2407.03901
In recent years, neural network-driven image compression (NIC) has gained significant attention. Some works adopt deep generative models such as GANs and diffusion models to enhance perceptual quality (realism). A critical obstacle of these generativ
Externí odkaz:
http://arxiv.org/abs/2405.16817
Infrared (IR) image super-resolution faces challenges from homogeneous background pixel distributions and sparse target regions, requiring models that effectively handle long-range dependencies and capture detailed local-global information. Recent ad
Externí odkaz:
http://arxiv.org/abs/2405.09873
Autor:
Huang, Yongsong, Miyazaki, Tomo, Liu, Xiaofeng, Jiang, Kaiyuan, Tang, Zhengmi, Omachi, Shinichiro
Background and objective: High-resolution radiographic images play a pivotal role in the early diagnosis and treatment of skeletal muscle-related diseases. It is promising to enhance image quality by introducing single-image super-resolution (SISR) m
Externí odkaz:
http://arxiv.org/abs/2312.16455
Autor:
Huang, Yongsong, Omachi, Shinichiro
The ability of generative models to accurately fit data distributions has resulted in their widespread adoption and success in fields such as computer vision and natural language processing. In this chapter, we provide a brief overview of the applica
Externí odkaz:
http://arxiv.org/abs/2312.00689
Recent efforts have explored leveraging visible light images to enrich texture details in infrared (IR) super-resolution. However, this direct adaptation approach often becomes a double-edged sword, as it improves texture at the cost of introducing n
Externí odkaz:
http://arxiv.org/abs/2311.08816
Publikováno v:
Pattern Recognition, 2023
Image compression is a fundamental technology for Internet communication engineering. However, a high compression rate with general methods may degrade images, resulting in unreadable texts. In this paper, we propose an image compression method for m
Externí odkaz:
http://arxiv.org/abs/2305.11373
Image Super-Resolution (SR) is essential for a wide range of computer vision and image processing tasks. Investigating infrared (IR) image (or thermal images) super-resolution is a continuing concern within the development of deep learning. This surv
Externí odkaz:
http://arxiv.org/abs/2212.12322
Scene-text image synthesis techniques that aim to naturally compose text instances on background scene images are very appealing for training deep neural networks due to their ability to provide accurate and comprehensive annotation information. Prio
Externí odkaz:
http://arxiv.org/abs/2209.02397