activity
20192023
most citedSelf-Play Reinforcement Learning for Fast Image Retargeting

21 citations · 43 across the 4 of their papers we have counts for

collaborators
Showing cs.CVShow all

5 papers · 1 filter

cs.CV20236 cited

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…

cs.CV20237 cited

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…

cs.CV202021 cited

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…

cs.CV20199 cited

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.…

cs.CV2019

Object-Aware Instance Labeling for Weakly Supervised Object Detection

Satoshi Kosugi, Toshihiko Yamasaki, Kiyoharu Aizawa

Weakly supervised object detection (WSOD), where a detector is trained with only image-level annotations, is attracting more and more attention. As a method to obtain a well-perfor…