We created a virtual experience of TAKANAWA GATEWAY CITY using Movie Map technology in collaboration with JR East for TEAM EXPO 2025 at the Kansai Expo. We exhibited and held an experience session on October 11th.
News
- MOVIE MAP
- FOOD LOG
Track and analyze your daily food choices with our Food Log project!
- MANGA PROJECT
- LECTURES
Links for lectures.
- IEEE Student Branch
EXPO 2025 Exhibition
2025/10
Accepted for Multimedia Tools and Applications, Springer
2025/09
The following papers were accepted for MTAP.
- Building and Evaluating a Realistic Virtual World for Large Scale Urban Exploration from 360° Videos
Mizuki Takenawa, Naoki Sugimoto, Leslie Wöhler, Satoshi Ikehata, Kiyoharu Aizawa.
Accepted for Frontiers in Virtual Reality
2025/08
The following papers were accepted for Frontiers in Virtual Reality.
- Visual Attention and Cognitive Effects of Facial Anonymization in 360°Videos
Leslie Woehler, Satoshi Ikehata, Kiyoharu Aizawa.
Accepted for ACM Multimedia
2025/08
The following papers were accepted for ACM Multimedia2025.
- A Highly Clean Recipe Dataset with Ingredient States Annotation for State Probing Task
Mashiro Toyooka, Kiyoharu Aizawa, Yoko Yamakata - FoolLogAthl-218: Constructiong a Real-World Food Image Dataset Using Dietary Management Applications
Mitsuki Watanabe, Sosuke Amano, Kiyoharu Aizawa, Yoko Yamakata
Accepted for TMLLR
2025/07
The following paper was accepted for TMLLR2025.
- Generalized Out-of-Distribution Detection and Beyond in Vision Language Model Era: A Survey
Atsuyuki Miyai, Jingkang Yang, Jingyang Zhang, Yifei Ming, Yueqian Lin, Qing Yu, Go Irie, Shafiq Joty, Yixuan Li, Hai Helen Li, Ziwei Liu, Toshihiko Yamasaki, Kiyoharu Aizawa
Accepted for ACL
2025/05
The following papers were accepted for ACL2025.
- ACL Main
- Unsolvable Problem Detection: Robust Understanding Evaluation for Large Multimodal Models
Atsuyuki Miyai, Jingkang Yang, Jingyang Zhang, Yifei Ming, Qing Yu, Go Irie, Yixuan Li, Hai Li, Ziwei Liu, Kiyoharu Aizawa
- Unsolvable Problem Detection: Robust Understanding Evaluation for Large Multimodal Models
- ACL Findings
- Harnessing PDF Data for Improving Japanese Large Multimodal Models
Baek JeongHun, Akiko Aizawa, Kiyoharu Aizawa
- Harnessing PDF Data for Improving Japanese Large Multimodal Models
Accepted for ICIP
2025/05
The following papers were accepted for ICIP2025.
- A Benchmark and Evaluation for Real-World Out-of-Distribution Detection Using Vision-Language Models
Shiho Noda, Atsuyuki Miyai, Qing Yu, Go Irie, Kiyoharu Aizawa - Perface: Metric Learning in Perceptual Facial Similarity For Enhanced Face Anonymization
Haruka Kumagai, Leslie Wöhler, Satoshi Ikehata, Kiyoharu Aizawa