📝 Publications
Journal

Class-agnostic 3D Segmentation by Granularity-Consistent Automatic 2D Mask Tracking.
Juan Wang, Yasutomo Kawanishi, Tomo Miyazaki, Zhijie Wang, Shinichiro Omachi.
-The research advances annotation-free 3D instance segmentation by tracking 2D masks across video and training progressively, turning noisy frame-wise pseudo labels into coherent 3D supervision for accurate, open-vocabulary results.

TAMC: Textual Alignment and Masked Consistency for Open-Vocabulary 3D Scene Understanding.
Juan Wang, Zhijie Wang, Tomo Miyazaki, Yaohou Fan, Shinichiro Omachi.
- The research improves 3D scene understanding through masked consistency training and pseudo-text labels, effectively addressing sparse point cloud processing and training-inference inconsistency issues.

An end-to-end deep neural network is proposed to detect aluminum profile defects \ Wang J, Meng Z H.
- Proposed a Deformable Feature Pyramid module to detect aluminum profile defects.
Conference
ICONIP 2025Scene Text Reconstructor: A Contextual-Aware Masking Framework for Pre-training Text Detectors(Soptlight). Yaohou Fan, Tomo Miyazaki, Zhengmi Tang, Juan Wang, Yongsong Huang, Shinichiro Omachi. 32nd International Conference on Neural Information Processing 35th Annual Meeting of Japanese Neural Network Society.MIRU 2025Class-Agnostic 3D Segmentation without Manual Labels by 2D Mask Tracking. Juan Wang, Yasutomo Kawanishi, Zhijie Wang, Tomo Miyazaki, Shinichiro Omachi. 画像の認識・理解シンポジウム MIRU, 2025.-
MIRU 2024Improved Open-Vocabulary 3D Scene Understanding via Masked Feature Alignment. Juan Wang, Zhijie Wang, Tomo Miyazaki, Shinichiro Omachi. 画像の認識・理解シンポジウム MIRU, 2024.