21 citations · 56 across the 7 of their papers we have counts for
7 papers
Leveraging the Powerful Attention of a Pre-trained Diffusion Model for Exemplar-based Image Colorization
Satoshi Kosugi
Exemplar-based image colorization aims to colorize a grayscale image using a reference color image, ensuring that reference colors are applied to corresponding input regions based…
Prompt-Guided Image-Adaptive Neural Implicit Lookup Tables for Interpretable Image Enhancement
Satoshi Kosugi
In this paper, we delve into the concept of interpretable image enhancement, a technique that enhances image quality by adjusting filter parameters with easily understandable names…
Personalized Image Enhancement Featuring Masked Style Modeling
Satoshi Kosugi, Toshihiko Yamasaki
We address personalized image enhancement in this study, where we enhance input images for each user based on the user's preferred images. Previous methods apply the same preferred…
Crowd-Powered Photo Enhancement Featuring an Active Learning Based Local Filter
Satoshi Kosugi, Toshihiko Yamasaki
In this study, we address local photo enhancement to improve the aesthetic quality of an input image by applying different effects to different regions. Existing photo enhancement…
Self-Play Reinforcement Learning for Fast Image Retargeting
Nobukatsu Kajiura, Satoshi Kosugi, Xueting Wang +1
In this study, we address image retargeting, which is a task that adjusts input images to arbitrary sizes. In one of the best-performing methods called MULTIOP, multiple retargetin…
Unpaired Image Enhancement Featuring Reinforcement-Learning-Controlled Image Editing Software
Satoshi Kosugi, Toshihiko Yamasaki
This paper tackles unpaired image enhancement, a task of learning a mapping function which transforms input images into enhanced images in the absence of input-output image pairs.…