The 29th International Workshop on Frontiers of Computer Vision(IW-FCV 2023)
February 20-22, 2023, Yeosu, Utop Marina Hotel, South Korea
https://iwfcv2023.github.io/

Program Guidebook|Organized by |IW-FCV 2023 Organizing Committee|Co-organized by |Culture Technology Institute, Chonnam National University
Korean Institute Smart MediaCNU National Program of Excellence in Software|Sponsor by |JeollaNamdo Tourism Organization
Yeosu City
Korean Computer Vision Society
https://iwfcv2023.github.io/

Contents
Welcome message from General Chairs ················································································· 03

Call for Papers ··························································································································· 04

Sponsors ···································································································································· 05

Organizing Committee ·············································································································· 06

Workshop Venue ······················································································································ 10

Keynote Speech-1 ····················································································································· 11

Keynote Speech-2 ····················································································································· 12Time Table ································································································································· 13

Presentation Program ·············································································································· 142

https://iwfcv2023.github.io/

Welcome message from General Chairs
We would like to warmly welcome you all to IW-FCV 2023(International Workshop
on Frontiers of Computer Vision) to be held in Yeosu, Korea from February 20th to 22nd,
2023. It is an honor to serve as the General Chair of this esteemed event and we arethrilled to see so many participants from around the world come together to exchange
knowledge and share their research results.
As many of you may know, this international workshop has a rich history, initiallystarted as a platform for research exchange between Japanese and Korean computer visionresearchers. It has been held every year for 29 years and despite the challenges posed by
the Covid-19 pandemic, we are proud to have maintained this tradition for the past three
years through the efforts of many dedicated researchers. This year, we are particularly
thrilled to be able to hold the event face-to-face in the beautiful city of Yeosu, Korea.
Computer Vision is a field that has recently received a great deal of attention in the
AI field. It is a source of technology for the development of high value-added products
and systems such as autonomous vehicle, intelligent surveillance systems, robots, andhigh-quality movies. Researchers in this field aim to mimic human visual functions withcomputers and through their efforts, high-level problems that were previously considereddifficult are now being solved using deep learning techniques. The significance ofcomputer vision research cannot be overstated, and we hope that young researchers fromaround the world will continue to participate in this workshop and contribute to its growth.
In addition to the intellectual stimulation that this workshop provides, we also hope thatyou will take the time to enjoy the beauty of Yeosu. This port city is located at thesouthern tip of Korea and is famous for its clean water and delicious southern Korean
cuisine made with. Yeosu has a rich history of overseas trade and is well-known for its
prosperity. The coast of Yeosu is also a stunning sight with its small islands, including
Dongbaek-island and Hyangil-temple.
Lastly, I would like to express my sincere gratitude to the researchers who submitted
papers for this workshop, the organizing committee members, and the members of theSteering Committee who have worked tirelessly to make this event possible. Your
contributions and dedication are greatly appreciated.
Thank you for your participation and I hope you have a wonderful and productive
time at IW-FCV2023 in Yeosu, Korea.
General Chairs of IW-FCV 2023

Prof. Chilwoo LEE

Prof. Kazuhiko SUMI

https://iwfcv2023.github.io/3

Call for Paper

4

https://iwfcv2023.github.io/

Sponsors
Korean Computer
Vision Society
JeollaNamdo Turism
Organization
Yeosu City

Organizers
IW-FCV 2023 Committee

IW-FCV 2023 Committee
CNU National Program of
Excellence in Software

Korean Institute
Smart Media
Culture Technology Institute,

Culture Technology Institute,Chonnam National University

Chonnam National University

https://iwfcv2023.github.io/5

Steering Committee
Name

Affiliation

Yoshimitsu Aoki

Keio University

Hiroyasu Koshimizu

YYC-Solution

Takio Kurita

Hiroshima University

Chikahito Nakajima

CRIEPI

Makoto Niwakawa

Meidensha

Rin-ichiro Tanaguchi

Kyushu University

Kazuhiko Yamamoto

Gifu University

Jun-ichiro Hayashi

Kagawa University

Kazuhiko Sumi

Aoyama Gakuin University

Kanghyun Jo

University of Ulsan

Soon Ki Jung

Kyungpook National University

Chilwoo Lee

Chonnam National University

Weon-Geun Oh

ETRIJong-Il Park

Hanyang University

Inseop Na

Chosun University

Hieyong Jeong

Chonnam National University

Kiryong Kwon

Bukyung National University

Organizing Committee
General Chairs
Chilwoo Lee

Chonnam National University

South Korea

Kazuhiko Sumi

Aoyama Gakuin University

Japan

Program Chairs
Inseop Na

Chosun University

South Korea

Go Irie

Tokyo University of ScienceJapan

Financial Chair
Daejin Kim

6Chonnam National University
https://iwfcv2023.github.io/

South Korea

Publication Chair
Hieyong Jeong

Chonnam National University

South Korea

Publicity Chair
Kyungbaek Kim

Chonnam National University

South Korea

Local Arrangement Chair
Chunseong Shin

Chonnam National University

South Korea

Web Chair
Inseop Na

Chosun University

South Korea

Program Committee
Name

Affiliation

Nationality

Kaushik Deb

Chittagong University of Engineering andTechnology

Bangladesh

Van-Dung Hoang

Quangbinh University

VietnamMd Zahidul Islam

Islamic University, Kushtia

Bangladesh

Moon-Ho Jeong

Kwangwoon University

South Korea

Hyun-Deok Kang

UNISTSouth Korea

Jail Kim

Kyungpook National University

South Korea

Soo Hyung Kim

Chonnam National University

South Korea

Wonjun Kim

Konkuk University

South Korea

My Ha Le

Ho Chi Minh City University of Education

Vietnam

Chul Lee

Dongguk University

South Korea

Jae-Ho Lee

ETRISouth Korea

Suk Hwan Lee

Tong Myong University

South Korea

Hoang-Hon Trinh

Ho Chi Minh City University of Technology

Japan

Ming-Hsuan Yang

University of California at MercedUSA

Byoung-Ju Yun

Kyungpook National University

South Korea

Wahyono S.Kim

Gadja Mada University

Indonesia

https://iwfcv2023.github.io/

7

8

Name

Affiliation

Nationality

Kwanghee Won

South Dakota State University

USA

Takayuki Fujiwara

Hokkaido Information University

Japan

Yoshinori Kuno

Saitama University

Japan

Hidehiro Ohki

Oita University

Japan

Hideo Saito

Keio University

Japan

Atsushi Shimada

Kyushu University

Japan

Kenji Terada

Tokushima University

Japan

Yasutomo Kawanishi

Nagoya University

Japan

Takayoshi Yamashita

Chubu University

Japan

Hironobu Fujiyoshi

Chubu University

Japan

Kengo Terasawa

Future University Hakodate

Japan

Toru Tamaki

Hiroshima University

Japan

Diego Thomas

Kyushu University

Japan

Maiya Hori

Kyushu University

Japan

Michihiro Mikamo

Kagoshima University

Japan

Kazuhiko Sumi

Aoyama Gakuin University

Japan

Hiroshi Tanaka

Fujitsu Laroratories Ltd.

Japan

Keiji Yanai

University of Electro-Communications

Japan

Hitoshi Habe

Kindai University

Japan

Shiuichi Akizuki

Chukyo University

Japan

Masakazu Lwamura

Osaka Prefecture University

Japan

Gou Koutaki

Kumamoto University

Japan

Masashi Nishiyama

Tottori University

Japan

Wataru Ohyama

Siatama Institute of Technology

Japan

Takahiro Okabe

Kyushu Institute of Technology

Japan

Tsubasa Minematsu

Kyushu University

Japan

https://iwfcv2023.github.io/

Reviewers
Name

Email

Hiroaki Aizawa
Shuichi Akizuki
Jun Fujiki
Takayuki Fujiwara
Ryosuke Furuta
Hitoshi Habe
Vandung Hoang
Maiya Hori
Hae-Gon Jeon
Hieyong Jeong
Kanghyun Jo
Soonki Jung
Naoshi Kaneko
Gou Koutaki
Takio Kurita
Chilwoo Lee
Sang Hwa Lee
Seokju Lee
Suk-Hwan Lee
Tsubasa Minematsu
Yu Mitsuzumi
Minoru Mori
Katsuyuki Nakamura
Kazuaki Nakamura
Masashi Nishiyama
Wataru Ohyama
Takahiro Okabe
Yuji Oyamada
Hanhoon Park
Takashi Shibata
Inwook Shim
Yongqing Sun
Toru Tamaki
Yukinobu Taniguchi
Kengo Terasawa
Diego Thomas
Xiaomeng Wu
Yota Yamamoto
Keiji Yanai

hiroaki-aizawa@hiroshima-u.ac.jp
s-akizuki@sist.chukyo-u.ac.jp
fujiki@fukuoka-u.ac.jp
tfuji@do-johodai.ac.jp
furuta@iis.u-tokyo.ac.jp
habe@habe-lab.org
dungvanhoang@gmail.com
m-hori@kankyo-u.ac.jp
haegonj@gist.ac.kr
h.jeong@jnu.ac.kr
acejo@ulsan.ac.kr
skjung@knu.ac.kr
kaneko@it.aoyama.ac.jp
koutaki@cs.kumamoto-u.ac.jp
tkurita@hiroshima-u.ac.jp
leecw@jnu.ac.kr
lsh529@snu.ac.kr
slee@kentech.ac.kr
skylee@dau.ac.kr
minematsu.tsubasa.659@m.kyushu-u.ac.jp
yu.mitsuzumi.ae@hco.ntt.co.jp
mmori@ic.kanagawa-it.ac.jp
katsuyuki.nakamura.xv@hitachi.com
nakamura.kazuaki@rs.tus.ac.jp
nishiyama@eecs.tottori-u.ac.jp
w.ohyama@mail.dendai.ac.jp
okabe@ai.kyutech.ac.jp
oyamada@tottori-u.ac.jp
hanhoon_park@pknu.ac.kr
t.shibata@ieee.org
iwshim@inha.ac.kr
yongqingsun.li@gmail.com
tamaki.toru@nitech.ac.jp
taniguchi.yukinobu@rs.tus.ac.jp
kterasaw@fun.ac.jp
thomas@ait.kyushu-u.ac.jp
xiaomeng.wu.px@hco.ntt.co.jp
yy-yamamoto@rs.tus.ac.jp
yanai@cs.uec.ac.jp

https://iwfcv2023.github.io/

9Workshop Venue
Workshop Venue:
Utop Marina Hotel, Yeosu, South Korea.

Address:
Odongdo-ro 61-15, Yeosu, Jeollanamdo (Sujeong-dong 777-1)
Tel: +82-61-690-8000
E-mail:utopmarina.yeosu@gmail.com

910

https://iwfcv2023.github.io/

Keynote Speech_1
Title: Deep Attention Models for Object
Recognition
Speaker: Dr. In So Kweon, KAIST, South Korea

Abstract
In recent years, the performance of Deep Learning based approaches for object recognition
has improved dramatically and even surpassed human performance in some benchmarking
datasets. Specifically, Deep attention models have been very effective to improve recognition
performance. In this talk, we present two convolutional attention models inspired by humanvisual systems, in which the object is defined by the presence or absence of “Local Visual
Properties” and by “object parts” with their “Contextual Relations”. We also present a simple
and effective video mask transformer model that is widely applicable to multiple video
segmentation tasks. TubeFormer-DeepLab directly predicts video tubes with task-specific labels(either pure semantic categories, or both semantic categories and instance identities), which not
only significantly simplifies video segmentation models, but also advances state-of-the-art resultson multiple video segmentation benchmarks.

Biography
Professor In So Kweon received the B.S. and the M.S. degrees in Mechanical Design and
Production Engineering from Seoul National University, Korea, in 1981 and 1983, respectively,
and the Ph.D. degree in Robotics from the Robotics Institute at Carnegie Mellon University in1990. He worked for Toshiba R&D Center and joined KAIST in 1992. He is a KEPCO Chair
professor of the School of Electrical Engineering and had been the director for the National Core
Research Center – P3 DigiCar Center at KAIST (2010~2017). His research focuses on
Computer Vision and Robotics. He has published 3 research books, and more than 500 papers inleading journals and conference proceedings, including 100+ in prestigious CVPR, ICCV, and
ECCV. He is also active in professional service. Currently, he is the President of the Asia
Federation of Computer Vision (AFCV). He served on the Editorial Board of the International
Journal of Computer Vision for ten years since 2005. He has also organized 5 international
conferences either as a general chair or a program chair, including IEEE-CVF ICCV 2019. He
was awarded “2016 Faculty Research Excellence Award”, “2020 Grand Prize for Academic
Excellence”, and “2021 Hyung-Gyu Im LINKGENESIS Best Teacher Award” by KAIST andconferred a Prime Minister Award by the Korean Government for his contribution to
DRC-HUBO+ to win the DARPA Robotics Challenge in 2015. He also received several awards
from international conferences, including "The Best Paper Award of the IEEE Transaction on
CSVT 2014" and "The Best Student Paper Runnerup Award in the IEEE-CVPR 2009".

https://iwfcv2023.github.io/

11

Keynote Speech_2
Title: Pre-training without Natural Images
Speaker: Dr. Hirokatsu Kataoka, AIST, Japan

Abstract
The talk introduces a novel concept called Formula-driven Supervised Learning (FDSL) for
using convolutional neural networks and vision transformers pre-trained without real images forreal image recognition. Instead of real images, the pre-training phase employs fractals/contours
generated from mathematical formulas as image patterns and their category labels, allowing for
an infinitely large labeled image dataset. The proposed FDSL framework differs from otherlearning strategy like self-supervised learning, and doesn't require defining object categories andpreparing real images. The experimental results show that FDSL pre-training outperforms somepre-trained models and captures unique features in a model visualization.

Biography
Hirokatsu Kataoka received his Ph.D. in engineering from Keio University in 2014. His
research experience includes visiting scientist at Technical University of Munich (TUM) and
JSPS Fellow (PD) at the University of Tokyo. Currently, he is a Chief Senior Researcher at
National Institute of Advanced Industrial Science and Technology (AIST). He also leads the
cvpaper.challenge which conducts comprehensive survey and collaborative research in the fieldof computer vision and related academic fields. His research interest includes computer visionand pattern recognition, especially in large-scale dataset for image and video recognition. He hasreceived ACCV 2020 Best Paper Honorable Mention Award, AIST 2019 Best Paper Award, and
ECCV 2016 Workshop Brave New Idea.

12

https://iwfcv2023.github.io/

Time Table
Feb. 20th
8:30~

Registration

9:00~10:40

Oral Session 1

10:40~11:00

Coffee Break

11:00~11:20

Opening Ceremony

1F, Grand Ballroom

11:20~12:20

Keynote Speech 1

1F, Grand Ballroom

12:20~13:30

Lunch

B1, The Waven

12:20~14:30

Poster Session 1

2F, Greenwich Hall

14:30~16:10

Oral Session 2

1F, Grand Ballroom

16:10~16:30

Coffee Break

16:30~18:10

Oral Session 3

1F, Grand Ballroom

1F, Grand Ballroom

Feb. 21st
8:30~

Registration

9:00~11:00

Oral Session 4

11:00~11:20

Coffee Break

11:20~12:20

Keynote Speech 2

1F, Grand Ballroom

12:20~13:30

Lunch

B1, The Waven

12:20~14:30

Poster Session 2

2F, Greenwich Hall

14:30~16:30

Oral Session 5

1F, Grand Ballroom

16:30~16:50

Coffee Break

16:50~18:10

Oral Session 6

18:10~18:30

Coffee Break

18:30~20:30

Banquet & Award Ceremony

1F , Grand Ballroom

09:00~

Technical Tour

Departure
Hotel Main Gate

12:00~

Workshop Board Meeting

Utop Marina Hotel & Resort

1F, Grand Ballroom

1F, Grand Ballroom

Feb. 22ndhttps://iwfcv2023.github.io/

13

Presentation Program
Oral Session 1(Recognition A)

Feb. 20th, 2023
09:00 ~ 10:40

Session
ChairsDr. Kanghyun Jo,
Dr. Go Irie

O1-1

Hierarchical Image Classification with Conceptual Hierarchies
Generated via Lexical Databases

Tomoaki Yamazaki, Seiya Ito andKouzou Ohara

O1-2

Action Recognition for Each Person with
Large-scale Object Detector

Akira Mitsuoka and Kunihito Kato

O1-3

Structural Point Cloud Data Recovery to Learning 3D Feature
Representation

Ryosuke Yamada, Ryu Tadokoro, Yue
Qiu, Hirokatsu Kataoka and Yutaka
Satoh

O1-4

Point Cloud Based Deep Molecular Pose Estimation for
Structure-Based Virtual Screening

Ken Kariya, Go Irie, Ryosuke Furuta,
Yota Yamamoto, Shin Aoki and
Yukinobu Taniguchi

O1-5

Efficient Multi-Receptive Pooling for Object Detection on Drone

Jinsu An, Dwisnanto Muhamad Putro,
Adri Priadana and Kanghyun Jo.

Oral Session 2(Image Analysis)

Feature Extraction by

Feb. 20th, 2023
14:30 ~ 16:10

Session
ChairsDr. Hae-Gon Jeon, Dr.
Yuji Pyamada

Robust Scene Text Detection under Occlusion via Multi-Scale
Adaptive Deep Network

My-Tham Dinh, Minh-Trieu Tran,
Quang-Vinh Dang and Guee-Sang Lee

O2-2

Detection and Tracking of Flying Small Bats under Complex
Backgrounds

Kakeru Sugimoto, Kazusa Ushio,
Ryota Sugimori, Emyo Fujioka,
Hiroaki Kawashima, Shizuko Hiryu
and Hitoshi Habe

O2-3

Facial Depth and Normal Estimation using Single Dual-Pixel
CameraMinjun Kang, Jaesung Choe, Hyowon
Ha, Hae-Gon Jeon, Sunghoon Im, In
So Kweon and Kuk-Jin Yoon

O2-4

Generative Bias for Robust Visual Question Answering

Jae Won Cho, Dong-Jin Kim,
Hyeonggon Ryu and In So Kweon

O2-5

DDConv: Dilated Depthwise Convolution with YOLOv5 forDrone Imagery

Jehwan Choi, Minseung Kim, Donggue
Kim and Kang-Hyun Jo

O2-1

14

https://iwfcv2023.github.io/Oral Session 3(Image Fundamental)

Feb. 20th, 2023
16:30 ~ 18:10

Session
ChairsDr. Dong-Geol Choi,
Dr. Hiroaki aizawa

O3-1

DASO: Distribution-Aware Semantics-Oriented Pseudo-label for
Imbalanced Semi-Supervised Learning

Youngtaek Oh, Dong-Jin Kim and In
So Kweon

O3-2

Improvement of Robustness to Noise for Medical Image
Segmentation by using Self-Supervised Learning Approach

Yuta Konishi and Takio Kurita

O3-3

Bidirectional Domain Mixup for Domain Adaptive Semantic
Segmentation

Minseok Seo, Yuhyun Kim andDong-Geol Choi

O3-4

LabOR: Labeling Only if Required for Domain Adaptive Semantic
Segmentation

Inkyu Shin, Dong-Jin Kim, Jae Won
Cho, Sanghyun Woo, Kwanyong Parkand In So Kweon

O3-5

Attribute Auxiliary Clustering for Person Re-identification

Ge Cao and Kanghyun Jo

Poster Session 1

Feb. 20th, 2023
12:20~14:30

Session
ChairsDr. Choonsung Shin,Dr. Yota Yamamoto

P1-1

Format-Compatible 3D Metahuman Modeling from a Single
Image

So Jin Yun, Soyoung Yoon and In Kyu
Park

P1-2

YOLO5PKLot: A Parking Lot Detection Network Based on
Improved YOLOv5 for Smart Parking Management System

Duy-Linh Nguyen, Xuan-Thuy Vo,
Adri Priadana and Kang-Hyun Jo

P1-3

Texture Synthesis Based on Aesthetic Texture Perception Using
CNN Style and Content Features

Yukine Sugiyama, Natsuki Sunda,
Kensuke Tobitani and Noriko Nagata

P1-4

Emotion Recognition by using optimised deep features

Irfan Haider, Soo-Hyung Kim,
Hyung-Jeong Yang and Guee-Sang
Lee.

P1-5

Monitoring Students’ Classroom Attention on Digital Platform

Hirotoshi Ibe and Hiromasa Nakatani

P1-6

Patent Image Retrieval Using Cross-entropy-based Metric
Learning

Kotaro Higuchi, Yuma Honbu and
Keiji Yanai

P1-7

Pre-training of Pneumonia Classifier for Chest CT images using
Fractal Database

Yuken Yoshioka, Daichi Ikefuji,
Tomokazu Funatsu, Takashi Nagaoka,
Takenori Kozuka, Mitsutaka Nemoto,
Takahiro Yamada, Yuichi Kimura,
Kazunari Ishii and Hitoshi Habe

P1-8

Advanced Video Inpainting method using Residual Query
Connection

Youngjun La and Jong-Il Parkhttps://iwfcv2023.github.io/

15

Poster Session 1

Feb. 20th, 2023
12:20~14:30

Session
ChairsDr. Choonsung Shin,Dr. Yota Yamamoto

P1-9

Utilization of Temporal Detection Consistency for Improving theMulti-Object Tracking

Abhyudaya Singh Tak and Soon Ki
Jung

P1-10

A Study on Tracking Moving Objects: Pig counting with
YOLOv5 and StrongSORT

Seunggwan Lee, Wonhaeng Lee andJunghoon Park
Atsushi Kimura, Ryo Kawahara and
Takahiro Okabe

P1-11 BRDF Measurement with TDCRA

P1-12

Multi-scale Recurrent Residual U-Net for Anomaly Segmentationin Industrial Images

Haoyu Chen, Shivani Kolekar andKyungbaek Kim

P1-13

LHFAN: Scene Text Recognition Method Based on Multi-level
Feature Fusion and Enhancement of Semantic Knowledge

Ruturaj Mahadshetti, Guee-Sang Lee,
Hyung-Jeong Yang and Soo-Hyung
Kim

P1-14

Preliminary Study on Fish Tracking in Indoor Aquaculture
through Deep Learning

Nguyen Ngoc Huynh, Hieyong Jeong,
Myoungjae Jun, Hang Thi Phuong
Nguyen and Choonsung Shin

P1-15

Front Cover Image Database of Japanese Manga and Typeface
Estimation of their Title

Shota Ishiyama, Kosuke Sakai andMinoru Mori

P1-16 Robotics Education under Pandemic Lockdown Situation.

Danilo Caceres-Hernandez, Vicente
González-Diaz, Kelvin Kung-Gomez
and Kang-Hyun Jo.

Lane Detection using Canny Edge Detection Algorithm for
P1-17
Real-time Racing Game

Sehar Shahzad Farooq, Hameedur
Rahman, Samiya Abdul Wahid,
Iftikhar Ahmad, Jin Ho Lee and Soon
Ki Jung

P1-18

16

Influence Analysis of Each Facial Region on Facial Expressions
Recognition

Min Sol Park and In Seop Na

https://iwfcv2023.github.io/Oral Session 4(Recognition B)

Feb. 21st, 2023
09:00 ~ 11:00

Session
ChairsDr. Inseop Na,
Dr. Hitoshi Habe

O4-1

UDA-COPE: Unsupervised Domain Adaptation for
Category-level Object Pose Estimation

Taeyeop Lee, Byeong-Uk Lee, Inkyu
Shin, Jaesung Choe, Ukcheol Shin, In
So Kweon and Kuk-Jin Yoon

O4-2

Dynamic Circular Convolution for Image Classification

Xuan-Thuy Vo, Duy-Linh Nguyen,
Adri Priadana and Kang-Hyun Jo

O4-3

Task-specific Scene Structure Representations

Seunghyun Shin, Jisu Shin and
Hae-Gon Jeon

O4-4

Learning Depth from Focus in the Wild

Changyeon Won and Hae-Gon Jeon

O4-5

Human Face Detector with Gender Identification by Split-based
Inception Block and Regulated Attention Module

Adri Priadana, Muhamad Dwisnanto
Putro, Duy-Linh Nguyen, Xuan-Thuy
Vo and Kang-Hyun Jo

O4-6

Novel Surveillance System for Suspicious Activities Analysis
using Deep Learning

Bhavana Kaushik.

Oral Session 5(Application A)

Feb. 21st, 2023
14:30 ~ 16:30

Session
ChairsDr. Soon Ki Jung, Dr.
Bhavana KaushikO5-1

3D structure extraction and evaluation of microvessels in cardiac
tissue imaged by confocal microscopy

Shotaro Kaneko, Yuichiro Arima,
Masahiro Migita and Masashi Toda

O5-2

Multi-Attributed Face Synthesis for One-Shot Deep Face
Recognition

Muhammad Shaheryar, Lamyanba
Laishram, Jong Taek Lee and Soon Ki
Jung

O5-3

Parallax-based Imitation Learning with Human Intervention for
Uncertain Insertion Tasks

Yasuharu Niwa, Kunihito Kato,
Hiroaki Aizawa, Yoshiyuki Hatta andKazuaki Ito

O5-4

A Style-based Caricature Generator

Lamyanba Laishram, Muhammad
Shaheryar, Jong Taek Lee and Soon Ki
Jung

O5-5

Detecting Mounting Behaviors of Dairy Cows by Pre-Training
with Pseudo Images

Yuta Okuda, Yota Yamamoto, Kazuaki
Nakamura and Yukinobu Taniguchi

O5-6

Classification of Lung and Colon Cancer Using Deep
MethodMd. Al-Mamun Provath, Kaushik Deb
and Kang-Hyun Jo

Learning

https://iwfcv2023.github.io/

17

Oral Session 6(Applications B)

Feb. 21st, 2023
16:45~18:05

Session
ChairsDr. Jongil Park,
Dr. Kazuhiko Sumi

O6-1

Reproduction of Artwork on Display using Hyperspectral
Imaging and Monitor Calibration

Kyudong Sim and Jong-Il Park

O6-2

Game Engine Compatible 3D Clothes Modeling from aSingle Image

Soyoung Yoon, So Jin Yun and In Kyu
Park

O6-3

Event-Based Reflectance Separation

Ryota Kunimasu, Ryo Kawahara and
Takahiro Okabe

O6-4

A Set of Control Points Conditioned Pedestrian Trajectory
Prediction

Inhwan Bae and Hae-Gon Jeon

Poster Session 2

Feb. 21st, 2023
12:20~14:30

Session
ChairsDr. Jeong Hieyong

P2-1

Diffuse Large B-cell Lymphoma Survival Prediction using
Encoding Clinical Features

Sy-Phuc Pham, Sae-Ryung Kang,
Hyung-Jeong Yang, Deok-Hwan Yang,
Sudarshan Pant, Soo-Hyung Kim andGuee-Sang Lee

P2-2

Robust Data Augmentation for Accurate Human Pose
Estimator

Tien Dat Tran, Xuan Thuy Vo, Adri
Priadana and Kang-Hyun Jo

P2-3

Multi-task model for glioma segmentation and isocitrate
dehydrogenase status prediction using segmentation
boundary

Xiaoyu Shi, Yinhao Li, Jingliang
Cheng, Jie Bai, Guohua Zhao and
Yen-Wei Chen

P2-4

Impression Estimation of Suit Patterns Based on Style
Features Using Multi-scale CNN

Eiki Tsumura, Kesnke Tobitani,
Miyuki Toga and Noriko Nagata

P2-5

A multi-layered structure of Pretrained Convolutional
Neural Network for weed classification

Gwang-Hyun Yu, Dang Thanh Vu,
Jeong Jaecheol, Chilwoo Lee andJinyoung Kim

P2-6

Two-stream Network for Moving Object Detection

Wisan Dhammatorn, Naoshi Kaneko,
Seiya Ito and Kazuhiko Sumi

18

https://iwfcv2023.github.io/

Poster Session 2

Feb. 21st, 2023
12:20~14:30

Session
ChairsDr. Jeong Hieyong

P2-7

Multimodal Transformer for Automatic Depression
Estimation System

Dang-Khanh Nguyen, Hyung-Jeong
Yang, Seung-Won Kim, Guee-Sang
Lee, Soo-Hyung Kim, Joo-Wan Kim
and Min Jhon

P2-8

Motion synthesis for automatic animation of sign language

Jongho Jeong, Chilwoo Lee, HeeJae
Hwang and Hongnyeom Sung

P2-9

Cattle Action Recognition with Multi-Viewpoint Cameras
based on Deep Learning

Muhammad Fahad Nasir, Alvaro
Fuentes, Shujie Han, Sook Yoon andDong Sun Park

P2-10
P2-11
P2-12
P2-13

Convolutional Neural Networks with Particle Swarm
Optimization: A Reliable Method for SARS-CoV-2
Detection in X-Ray Images
Multi-region based radial GCN algorithm for real-time
action recognition
Advanced Machine Learning Techniques To Identify
Emotions In Texts
Object pose estimation based on Template-matching using
attention module and residual block

Atif Ali
Hanbyul Jang and Chil-Woo Lee
Atif AliGa Eun Noh and Jong-Il Park

P2-14

COVID -19 detection based on CT Scan images using
Deep Learning methods

Tuan Le Dinh, Kim Jae-Huyn, Lee
Suk-Hwan and Kwon Ki-Ryong

P2-15

Enhanced Marathi Speech Recognition Using Double
Delta MFCC and DTW

Rajashri G Kanke and Manasi R Baheti

Change Detection Over Multispectral Images: A Case
P2-16
Study On RUSHIKONDA

Fyzulla Shaik, Pavan Kumar Chitturi S,
Pavan Veera Nagendra Kumar
Chintakayala and Surya Prakash
Punukollu

Gaussian Process based Illumination Planning for
Photometric Stereo
Data Generation and Deep Learning network for Micro
P2-18
Defect Detection
Classifying Breast Cancer Using Deep Convolutional
P2-19
Neural Network Method
P2-17

P2-20

Rough Target Region Extraction with Background
Learning

Yuji Oyamada
Byungjoon Kim and Yongduek Seo
Musfequa Rahman, Kaushik Deb andKang-Hyun Jo
Ryo Nakamura, Yoshiaki Ueda,
Masaru Tanaka and Jun Fujiki

https://iwfcv2023.github.io/

19

MEMO

20

https://iwfcv2023.github.io/

MEMO

https://iwfcv2023.github.io/

21

22

https://iwfcv2023.github.io/