| 2026 | AAAI | Difficulty Controlled Diffusion Model for Synthesizing Effective Training Data. | Zerun Wang, Jiafeng Mao, Xueting Wang, Toshihiko Yamasaki |
| 2025 | ICCV | Task-Specific Generative Dataset Distillation with Difficulty-Guided Sampling. | Mingzhuo Li, Guang Li, Jiafeng Mao, Linfeng Ye, Takahiro Ogawa, Miki Haseyama |
| 2025 | ICIP | Diversity-Driven Generative Dataset Distillation Based on Diffusion Model with Self-Adaptive Memory. | Mingzhuo Li, Guang Li, Jiafeng Mao, Takahiro Ogawa, Miki Haseyama |
| 2025 | ICIP | Noisy Label Refinement with Semantically Reliable Synthetic Images. | Yingxuan Li, Jiafeng Mao, Yusuke Matsui |
| 2024 | ECCV | The Lottery Ticket Hypothesis in Denoising: Towards Semantic-Driven Initialization. | Jiafeng Mao, Xueting Wang, Kiyoharu Aizawa |
| 2024 | ECCV | SCOMatch: Alleviating Overtrusting in Open-Set Semi-supervised Learning. | Zerun Wang, Liuyu Xiang, Lang Huang, Jiafeng Mao, Ling Xiao, Toshihiko Yamasaki |
| 2023 | ICIP | Training-Free Location-Aware Text-to-Image Synthesis. | Jiafeng Mao, Xueting Wang |
| 2023 | ICIP | Noise-Avoidance Sampling for Annotation Missing Object Detection. | Jiafeng Mao, Qing Yu, Go Irie, Kiyoharu Aizawa |
| 2021 | BMVC | Noisy Annotation Refinement for Object Detection. | Jiafeng Mao, Qing Yu, Yoko Yamakata, Kiyoharu Aizawa |
| 2020 | ICIP | Noisy Localization Annotation Refinement For Object Detection. | Jiafeng Mao, Qing Yu, Kiyoharu Aizawa |