activity
20182021
most citedDual Residual Networks Leveraging the Potential of Paired Operations for Image Restoration

17 citations · 31 across the 6 of their papers we have counts for

collaborators

10 papers

cs.CV20211 cited

Improved Few-shot Segmentation by Redefinition of the Roles of Multi-level CNN Features

Zhijie Wang, Masanori Suganuma, Takayuki Okatani

This study is concerned with few-shot segmentation, i.e., segmenting the region of an unseen object class in a query image, given support image(s) of its instances. The current met…

cs.CV2021

Matching in the Dark: A Dataset for Matching Image Pairs of Low-light Scenes

Wenzheng Song, Masanori Suganuma, Xing Liu +3

This paper considers matching images of low-light scenes, aiming to widen the frontier of SfM and visual SLAM applications. Recent image sensors can record the brightness of scenes…

cs.CV2021

Look Wide and Interpret Twice: Improving Performance on Interactive Instruction-following Tasks

Van-Quang Nguyen, Masanori Suganuma, Takayuki Okatani

There is a growing interest in the community in making an embodied AI agent perform a complicated task while interacting with an environment following natural language directives.…

eess.IV202012 cited

How Can CNNs Use Image Position for Segmentation?

Rito Murase, Masanori Suganuma, Takayuki Okatani

Convolution is an equivariant operation, and image position does not affect its result. A recent study shows that the zero-padding employed in convolutional layers of CNNs provides…

cs.CV2019

Efficient Attention Mechanism for Visual Dialog that can Handle All the Interactions between Multiple Inputs

Van-Quang Nguyen, Masanori Suganuma, Takayuki Okatani

It has been a primary concern in recent studies of vision and language tasks to design an effective attention mechanism dealing with interactions between the two modalities. The Tr…

cs.CV20191 cited

Analysis and a Solution of Momentarily Missed Detection for Anchor-based Object Detectors

Yusuke Hosoya, Masanori Suganuma, Takayuki Okatani

The employment of convolutional neural networks has led to significant performance improvement on the task of object detection. However, when applying existing detectors to continu…