Qing YU

About Me

Hi, my name is Qing YU. I am currently a research scientist at LY Corp. and a project researcher with The University of Tokyo, Japan. I am a member of Virtual Human Lab at LY Corp. I am also a member of Aizawa Labratory and working with Prof. Kiyoharu Aizawa. My research interest is in Computer Vision, including Motion Recognition, Motion Generation, Open-set Recognition and Domain Adaption. I was a recipient of Research Fellowships for Young Scientists (DC1) (2020-2023) and I was a recipient of The University of Tokyo Fellowship (2018-2020). I am most skilled in: Python and PyTorch. Full CV is here.

Publications

International Conferences

Qing Yu, Mikihiro Tanaka and Kent Fujiwara
ReMoGPT: Part-Level Retrieval-Augmented Motion-Language Models
AAAI Conference on Artificial Intelligence (AAAI), 2025.
Kent Fujiwara, Mikihiro Tanaka and Qing Yu
Chronologically Accurate Retrieval for Temporal Grounding of Motion-Language Models
European Conference on Computer Vision (ECCV), 2024.
[Website] [Paper] [Code]
Qing Yu, Mikihiro Tanaka and Kent Fujiwara
Exploring Vision Transformers for 3D Human Motion-Language Models with Motion Patches
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024.
[Website] [Paper] [Code]
Atsuyuki Miyai, Qing Yu, Go Irie and Kiyoharu Aizawa
LoCoOp: Few-Shot Out-of-Distribution Detection via Prompt Learning
Neural Information Processing Systems (NeurIPS), 2023.
[Paper] [Code]
Jiafeng Mao, Qing Yu, Go Irie and Kiyoharu Aizawa
Noise-Avoidance Sampling for Annotation Missing Object Detection
IEEE International Conference on Image Processing (ICIP), 2023.
[Paper]
Qing Yu and Kent Fujiwara
Frame-Level Label Refinement for Skeleton-Based Weakly-Supervised Action Recognition
AAAI Conference on Artificial Intelligence (AAAI), 2023.
[Paper] [Code]
Atsuyuki Miyai, Qing Yu, Daiki Ikami, Go Irie and Kiyoharu Aizawa
Rethinking Rotation in Self-Supervised Contrastive Learning: Adaptive Positive or Negative Data Augmentation
Winter Conference on Applications of Computer Vision (WACV), 2023.
[Paper] [Code]
Qing Yu, Daiki Ikami, Go Irie and Kiyoharu Aizawa
Self-Labeling Framework for Novel Category Discovery over Domains
AAAI Conference on Artificial Intelligence (AAAI), 2022.
[Paper] [Code]
Jiafeng Mao, Qing Yu, Yoko Yamakata and Kiyoharu Aizawa
Noisy Annotation Refinement for Object Detection
British Machine Vision Conference (BMVC), 2021.
[Paper]
Qing Yu, Atsushi Hashimoto and Yoshitaka Ushiku
Divergence Optimization for Noisy Universal Domain Adaptation
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
[Paper] [Code]
Qing Yu, Daiki Ikami, Go Irie and Kiyoharu Aizawa
Multi-Task Curriculum Framework for Open-Set Semi-Supervised Learning
European Conference on Computer Vision (ECCV), 2020.
[Paper] [Code]
Qing Yu and Kiyoharu Aizawa
Unknown Class Label Cleaning for Learning with Open-Set Noisy Labels
IEEE International Conference on Image Processing (ICIP), 2020.
[Paper] [Code]
Jiafeng Mao, Qing Yu and Kiyoharu Aizawa
Noisy Localization Annotation Refinement For Object Detection
IEEE International Conference on Image Processing (ICIP), 2020.
[Paper]
Takumi Kawashima, Qing Yu, Akari Asai, Daiki Ikami and Kiyoharu Aizawa
The Aleatoric Uncertainty Estimation Using a Separate Formulation with Virtual Residuals
International Conference on Pattern Recognition (ICPR), 2020.
[Paper]
Qing Yu and Kiyoharu Aizawa
Unsupervised Out-of-Distribution Detection by Maximum Classifier Discrepancy
IEEE International Conference on Computer Vision (ICCV), 2019.
[Paper] [Code]
Qing Yu, Masashi Anzawa, Sosuke Amano, Makoto Ogawa and Kiyoharu Aizawa
Food Image Recognition by Personalized Classifier
IEEE International Conference on Image Processing (ICIP), 2018.
[Paper]

Journal

Miyai Atsuyuki, Qing Yu, Go Irie and Kiyoharu Aizawa
GL-MCM: Global and Local Maximum Concept Matching for Zero-Shot Out-of-Distribution Detection
International Journal of Computer Vision, 2025.
[Paper] [Code]
Qing Yu, Go Irie and Kiyoharu Aizawa
Open-Set Domain Adaptation with Visual-Language Foundation Models
Computer Vision and Image Understanding, 2024.
[Paper]
Qing Yu, Go Irie and Kiyoharu Aizawa
Self-Labeling Framework for Open-Set Domain Adaptation with Few Labeled Samples
IEEE Transactions on Multimedia, 2023.
[Paper]
Jiafeng Mao, Qing Yu and Kiyoharu Aizawa
Noisy Localization Annotation Refinement for Object Detection
IEICE TRANS INF SYST, 2021.
Qing Yu, Masashi Anzawa, Sosuke Amano and Kiyoharu Aizawa
Personalized Food Image Classifier Considering Time-Dependent and Item-Dependent Food Distribution
IEICE TRANS INF SYST, 2019.

Preprints

Atsuyuki Miyai, Jingkang Yang, Jingyang Zhang, Yifei Ming, Yueqian Lin, Qing Yu, Go Irie, Shafiq Joty, Yixuan Li, Hai Li, Ziwei Liu, Toshihiko Yamasaki, Kiyoharu Aizawa
Generalized Out-of-Distribution Detection and Beyond in Vision Language Model Era: A Survey
arXiv, 2024.
[Paper] [Code]
Atsuyuki Miyai, Jingkang Yang, Jingyang Zhang, Yifei Ming, Qing Yu, Go Irie, Yixuan Li, Hai Li, Ziwei Liu, Kiyoharu Aizawa
Unsolvable Problem Detection: Evaluating Trustworthiness of Vision Language Models
arXiv, 2024.
[Paper] [Code]