Search Results for author: Masanori Suganuma

Found 24 papers, 12 papers with code

SBCFormer: Lightweight Network Capable of Full-size ImageNet Classification at 1 FPS on Single Board Computers

1 code implementation7 Nov 2023 Xiangyong Lu, Masanori Suganuma, Takayuki Okatani

For the first time, it achieves an ImageNet-1K top-1 accuracy of around 80% at a speed of 1. 0 frame/sec on the SBC.


That's BAD: Blind Anomaly Detection by Implicit Local Feature Clustering

no code implementations6 Jul 2023 Jie Zhang, Masanori Suganuma, Takayuki Okatani

They consider an unsupervised setting, specifically the one-class setting, in which we assume the availability of a set of normal (\textit{i. e.}, anomaly-free) images for training.

Anomaly Detection Clustering +1

Contextual Affinity Distillation for Image Anomaly Detection

no code implementations6 Jul 2023 Jie Zhang, Masanori Suganuma, Takayuki Okatani

The local student, which is used in previous studies mainly focuses on structural anomaly detection while the global student pays attention to logical anomalies.

Anomaly Detection Knowledge Distillation

Reference-based Motion Blur Removal: Learning to Utilize Sharpness in the Reference Image

no code implementations6 Jul 2023 Han Zou, Masanori Suganuma, Takayuki Okatani

We can utilize an alternative shot of the identical scene, just like in video deblurring, or we can even employ a distinct image from another scene.

Deblurring Image Deblurring

RefVSR++: Exploiting Reference Inputs for Reference-based Video Super-resolution

no code implementations6 Jul 2023 Han Zou, Masanori Suganuma, Takayuki Okatani

Then, we propose an improved method, RefVSR++, which can aggregate two features in parallel in the temporal direction, one for aggregating the fused LR and Ref inputs and the other for Ref inputs over time.

Reference-based Video Super-Resolution Video Super-Resolution

GRIT: Faster and Better Image captioning Transformer Using Dual Visual Features

1 code implementation20 Jul 2022 Van-Quang Nguyen, Masanori Suganuma, Takayuki Okatani

Current state-of-the-art methods for image captioning employ region-based features, as they provide object-level information that is essential to describe the content of images; they are usually extracted by an object detector such as Faster R-CNN.

Image Captioning

Rectifying Open-set Object Detection: A Taxonomy, Practical Applications, and Proper Evaluation

no code implementations20 Jul 2022 Yusuke Hosoya, Masanori Suganuma, Takayuki Okatani

In this paper, we first point out that the recent studies' formalization of OSOD, which generalizes open-set recognition (OSR) and thus considers an unlimited variety of unknown objects, has a fundamental issue.

Image Classification object-detection +2

Single-image Defocus Deblurring by Integration of Defocus Map Prediction Tracing the Inverse Problem Computation

no code implementations7 Jul 2022 Qian Ye, Masanori Suganuma, Takayuki Okatani

Considering the spatial variant property of the defocus blur and the blur level indicated in the defocus map, we employ the defocus map as conditional guidance to adjust the features from the input blurring images instead of simple concatenation.

Deblurring Image Deblurring +1

Learning Regularized Multi-Scale Feature Flow for High Dynamic Range Imaging

no code implementations6 Jul 2022 Qian Ye, Masanori Suganuma, Jun Xiao, Takayuki Okatani

Reconstructing ghosting-free high dynamic range (HDR) images of dynamic scenes from a set of multi-exposure images is a challenging task, especially with large object motion and occlusions, leading to visible artifacts using existing methods.

Vocal Bursts Intensity Prediction

Rethinking Unsupervised Domain Adaptation for Semantic Segmentation

2 code implementations30 Jun 2022 Zhijie Wang, Masanori Suganuma, Takayuki Okatani

Due to its high annotation cost, researchers have developed many UDA methods for semantic segmentation, which assume no labeled sample is available in the target domain.

Semantic Segmentation Unsupervised Domain Adaptation

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

no code implementations14 Sep 2021 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.

Cross-Region Domain Adaptation for Class-level Alignment

no code implementations14 Sep 2021 Zhijie Wang, Xing Liu, Masanori Suganuma, Takayuki Okatani

To cope with this, we propose a method that applies adversarial training to align two feature distributions in the target domain.

Semantic Segmentation Synthetic-to-Real Translation +1

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

no code implementations ICCV 2021 Wenzheng Song, Masanori Suganuma, Xing Liu, Noriyuki Shimobayashi, Daisuke Maruta, Takayuki Okatani

To consider if and how well we can utilize such information stored in RAW-format images for image matching, we have created a new dataset named MID (matching in the dark).

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

1 code implementation1 Jun 2021 Van-Quang Nguyen, Masanori Suganuma, Takayuki Okatani

It then integrates the prediction with the visual information etc., yielding the final prediction of an action and an object.

Instruction Following

How Can CNNs Use Image Position for Segmentation?

no code implementations7 May 2020 Rito Murase, Masanori Suganuma, Takayuki Okatani

We draw a mixed conclusion from the experimental results; the positional encoding certainly works in some cases, but the absolute image position may not be so important for segmentation tasks as we think.

Image Segmentation Medical Image Segmentation +3

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

1 code implementation ECCV 2020 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.

Visual Dialog

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

no code implementations21 Oct 2019 Yusuke Hosoya, Masanori Suganuma, Takayuki Okatani

The employment of convolutional neural networks has led to significant performance improvement on the task of object detection.

object-detection Object Detection

Restoring Images with Unknown Degradation Factors by Recurrent Use of a Multi-branch Network

1 code implementation10 Jul 2019 Xing Liu, Masanori Suganuma, Xiyang Luo, Takayuki Okatani

The employment of convolutional neural networks has achieved unprecedented performance in the task of image restoration for a variety of degradation factors.

Deblurring JPEG Artifact Removal +2

Hyperparameter-Free Out-of-Distribution Detection Using Softmax of Scaled Cosine Similarity

1 code implementation25 May 2019 Engkarat Techapanurak, Masanori Suganuma, Takayuki Okatani

The ability to detect out-of-distribution (OOD) samples is vital to secure the reliability of deep neural networks in real-world applications.

Metric Learning Out-of-Distribution Detection +1

Exploiting the Potential of Standard Convolutional Autoencoders for Image Restoration by Evolutionary Search

1 code implementation ICML 2018 Masanori Suganuma, Mete Ozay, Takayuki Okatani

Researchers have applied deep neural networks to image restoration tasks, in which they proposed various network architectures, loss functions, and training methods.

Image Restoration

A Genetic Programming Approach to Designing Convolutional Neural Network Architectures

5 code implementations3 Apr 2017 Masanori Suganuma, Shinichi Shirakawa, Tomoharu Nagao

To evaluate the proposed method, we constructed a CNN architecture for the image classification task with the CIFAR-10 dataset.

General Classification Image Classification +1

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