activity
20182021
most citedLearning from Synthetic Shadows for Shadow Detection and Removal

81 citations · 88 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV202181 cited

Learning from Synthetic Shadows for Shadow Detection and Removal

Naoto Inoue, Toshihiko Yamasaki

Shadow removal is an essential task in computer vision and computer graphics. Recent shadow removal approaches all train convolutional neural networks (CNN) on real paired shadow/s…

cs.CV2020

Augmented Cyclic Consistency Regularization for Unpaired Image-to-Image Translation

Takehiko Ohkawa, Naoto Inoue, Hirokatsu Kataoka +1

Unpaired image-to-image (I2I) translation has received considerable attention in pattern recognition and computer vision because of recent advancements in generative adversarial ne…

cs.CV20197 cited

PixelRL: Fully Convolutional Network with Reinforcement Learning for Image Processing

Ryosuke Furuta, Naoto Inoue, Toshihiko Yamasaki

This paper tackles a new problem setting: reinforcement learning with pixel-wise rewards (pixelRL) for image processing. After the introduction of the deep Q-network, deep RL has b…

cs.CV2018

Fully Convolutional Network with Multi-Step Reinforcement Learning for Image Processing

Ryosuke Furuta, Naoto Inoue, Toshihiko Yamasaki

This paper tackles a new problem setting: reinforcement learning with pixel-wise rewards (pixelRL) for image processing. After the introduction of the deep Q-network, deep RL has b…

cs.CV2018

Cross-Domain Weakly-Supervised Object Detection through Progressive Domain Adaptation

Naoto Inoue, Ryosuke Furuta, Toshihiko Yamasaki +1

Can we detect common objects in a variety of image domains without instance-level annotations? In this paper, we present a framework for a novel task, cross-domain weakly supervise…