Search Results for author: Yusuke Matsui

Found 24 papers, 14 papers with code

ZoDi: Zero-Shot Domain Adaptation with Diffusion-Based Image Transfer

no code implementations20 Mar 2024 Hiroki Azuma, Yusuke Matsui, Atsuto Maki

Deep learning models achieve high accuracy in segmentation tasks among others, yet domain shift often degrades the models' performance, which can be critical in real-world scenarios where no target images are available.

Domain Adaptation Image Segmentation +2

Theoretical and Empirical Analysis of Adaptive Entry Point Selection for Graph-based Approximate Nearest Neighbor Search

no code implementations7 Feb 2024 Yutaro Oguri, Yusuke Matsui

We present a theoretical and empirical analysis of the adaptive entry point selection for graph-based approximate nearest neighbor search (ANNS).

Novel Concepts

Cross-Lingual Learning in Multilingual Scene Text Recognition

1 code implementation17 Dec 2023 Jeonghun Baek, Yusuke Matsui, Kiyoharu Aizawa

We aim to find the condition that exploits knowledge from high-resource languages for improving performance in low-resource languages.

Scene Text Recognition

Relative NN-Descent: A Fast Index Construction for Graph-Based Approximate Nearest Neighbor Search

1 code implementation31 Oct 2023 Naoki Ono, Yusuke Matsui

For example, in experiments on the GIST1M dataset, the construction of the proposed method is 2x faster than NSG.

graph construction

General and Practical Tuning Method for Off-the-Shelf Graph-Based Index: SISAP Indexing Challenge Report by Team UTokyo

1 code implementation1 Sep 2023 Yutaro Oguri, Yusuke Matsui

Despite the efficacy of graph-based algorithms for Approximate Nearest Neighbor (ANN) searches, the optimal tuning of such systems remains unclear.

Manga109Dialog A Large-scale Dialogue Dataset for Comics Speaker Detection

1 code implementation30 Jun 2023 Yingxuan Li, Kiyoharu Aizawa, Yusuke Matsui

For further understanding of comics, an automated approach is needed to link text in comics to characters speaking the words.

Graph Generation Scene Graph Generation

Defense-Prefix for Preventing Typographic Attacks on CLIP

1 code implementation10 Apr 2023 Hiroki Azuma, Yusuke Matsui

In this study, we addressed the reduction of the impact of typographic attacks on CLIP without changing the model parameters.

object-detection Object Detection

Unbiased Scene Graph Generation using Predicate Similarities

no code implementations3 Oct 2022 Misaki Ohashi, Yusuke Matsui

The results of extensive experiments on the Visual Genome dataset show that the combination of our method and an existing debiasing approach greatly improves performance on tail predicates in challenging SGCls/SGDet tasks.

Descriptive Graph Generation +2

COO: Comic Onomatopoeia Dataset for Recognizing Arbitrary or Truncated Texts

1 code implementation11 Jul 2022 Jeonghun Baek, Yusuke Matsui, Kiyoharu Aizawa

To encourage research on this topic, we provide a novel comic onomatopoeia dataset (COO), which consists of onomatopoeia texts in Japanese comics.

Link Prediction Text Detection

Cascading Feature Extraction for Fast Point Cloud Registration

1 code implementation23 Oct 2021 Yoichiro Hisadome, Yusuke Matsui

We propose a method for speeding up a 3D point cloud registration through a cascading feature extraction.

Point Cloud Registration

What If We Only Use Real Datasets for Scene Text Recognition? Toward Scene Text Recognition With Fewer Labels

1 code implementation CVPR 2021 Jeonghun Baek, Yusuke Matsui, Kiyoharu Aizawa

To the best of our knowledge, this is the first study that 1) shows sufficient performance by only using real labels and 2) introduces semi- and self-supervised methods into STR with fewer labels.

Data Augmentation Scene Text Recognition

Building a Manga Dataset "Manga109" with Annotations for Multimedia Applications

3 code implementations9 May 2020 Kiyoharu Aizawa, Azuma Fujimoto, Atsushi Otsubo, Toru Ogawa, Yusuke Matsui, Koki Tsubota, Hikaru Ikuta

Manga, or comics, which are a type of multimodal artwork, have been left behind in the recent trend of deep learning applications because of the lack of a proper dataset.

Retrieval

Efficient Image Retrieval via Decoupling Diffusion into Online and Offline Processing

2 code implementations27 Nov 2018 Fan Yang, Ryota Hinami, Yusuke Matsui, Steven Ly, Shin'ichi Satoh

Diffusion is commonly used as a ranking or re-ranking method in retrieval tasks to achieve higher retrieval performance, and has attracted lots of attention in recent years.

Image Retrieval Re-Ranking +1

Reconfigurable Inverted Index

1 code implementation12 Aug 2018 Yusuke Matsui, Ryota Hinami, Shin'ichi Satoh

Owing to the linear layout, the data structure can be dynamically adjusted after new items are added, maintaining the fast speed of the system.

Object Detection for Comics using Manga109 Annotations

5 code implementations23 Mar 2018 Toru Ogawa, Atsushi Otsubo, Rei Narita, Yusuke Matsui, Toshihiko Yamasaki, Kiyoharu Aizawa

We annotated an existing image dataset of comics and created the largest annotation dataset, named Manga109-annotations.

Object object-detection +1

Region-Based Image Retrieval Revisited

no code implementations26 Sep 2017 Ryota Hinami, Yusuke Matsui, Shin'ichi Satoh

Second, to help users specify spatial relationships among objects in an intuitive way, we propose recommendation techniques of spatial relationships.

Attribute Image Retrieval +3

PQTable: Non-exhaustive Fast Search for Product-quantized Codes using Hash Tables

no code implementations21 Apr 2017 Yusuke Matsui, Toshihiko Yamasaki, Kiyoharu Aizawa

In this paper, we propose a product quantization table (PQTable); a fast search method for product-quantized codes via hash-tables.

Quantization

PQTable: Fast Exact Asymmetric Distance Neighbor Search for Product Quantization Using Hash Tables

no code implementations ICCV 2015 Yusuke Matsui, Toshihiko Yamasaki, Kiyoharu Aizawa

We propose the product quantization table (PQTable), a product quantization-based hash table that is fast and requires neither parameter tuning nor training steps.

Quantization

Sketch-based Manga Retrieval using Manga109 Dataset

no code implementations15 Oct 2015 Yusuke Matsui, Kota Ito, Yuji Aramaki, Toshihiko Yamasaki, Kiyoharu Aizawa

From the experiments, we verified that: (1) the retrieval accuracy of the proposed method is higher than those of previous methods; (2) the proposed method can localize an object instance with reasonable runtime and accuracy; and (3) sketch querying is useful for manga search.

Quantization Retrieval +1

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