| 2026 | AAAI | Adversarial Perturbation Shield: Preventing Concept Bleed-through in Continual Learning of Personalized Generative Models. | Ziwen Lan, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2025 | AISTATS | Hyperboloid GPLVM for Discovering Continuous Hierarchies via Nonparametric Estimation. | Koshi Watanabe, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2025 | ICASSP | Gradient-Oriented Clustered Federated Learning With Efficient Knowledge Sharing in Non-IID Settings. | Kenta Kubota, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2025 | ICASSP | Generative Dataset Distillation Based on Self-knowledge Distillation. | Longzhen Li, Guang Li, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2025 | ICASSP | Robust Adversarial Defense Based on Non-Transferability of Attack Across Foundation Models. | Koshiro Toishi, Keisuke Maeda, Ren Togo, Takahiro Ogawa, Miki Haseyama |
| 2025 | ICASSP | Triplet Synthesis for Enhancing Composed Image Retrieval via Counterfactual Image Generation. | Kenta Uesugi, Naoki Saito, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2025 | ICIP | Out-of-Distribution Sample Selection Generated by Diffusion Model toward Model Generalization. | Kaede Hayakawa, Keisuke Maeda, Ren Togo, Takahiro Ogawa, Miki Haseyama |
| 2025 | ICIP | Enhancing Adversarial Robustness of Foundation Models Without Data Centralization. | Koshiro Toishi, Keisuke Maeda, Ren Togo, Takahiro Ogawa, Miki Haseyama |
| 2025 | SiggraphA | MLLM-guided Training-free Spherical Panorama Generation from a Single Image. | Yuki Katayama, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2025 | SiggraphA | Lost in the Interface: How Structured UI Complexity Challenges Large Vision Language Models in Games. | Xiang Li, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2024 | CVPR | Generative Dataset Distillation: Balancing Global Structure and Local Details. | Longzhen Li, Guang Li, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2024 | ICASSP | Privacy Preserving Gaze Estimation Via Federated Learning Adapted To Egocentric Video. | Yuhu Feng, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2024 | ICASSP | Enhancing Noisy Label Learning Via Unsupervised Contrastive Loss with Label Correction Based on Prior Knowledge. | Masaki Kashiwagi, Keisuke Maeda, Ren Togo, Takahiro Ogawa, Miki Haseyama |
| 2024 | ICASSP | Multi-Object Editing in Personalized Text-To-Image Diffusion Model Via Segmentation Guidance. | Haruka Matsuda, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2024 | ICASSP | Caption Unification for Multi-View Lifelogging Images Based on In-Context Learning with Heterogeneous Semantic Contents. | Masaya Sato, Keisuke Maeda, Ren Togo, Takahiro Ogawa, Miki Haseyama |
| 2024 | ICIP | Cross-Domain Few-Shot In-Context Learning For Enhancing Traffic Sign Recognition. | Yaozong Gan, Guang Li, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2024 | ICIP | Reinforcing Pre-Trained Models Using Counterfactual Images. | Xiang Li, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2024 | SiggraphA | Generalizing Human Motion Style Transfer Method Based on Metadata-independent Learning. | Yuki Era, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2024 | SiggraphA | An Evaluation Metric for Single Image-to-3D Models Based on Object Detection Perspective. | Yuiko Uchida, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2023 | ICASSP | Improving Dropout in Graph Convolutional Networks for Recommendation via Contrastive Loss. | Hiroki Okamura, Keisuke Maeda, Ren Togo, Takahiro Ogawa, Miki Haseyama |
| 2023 | ICASSP | Estimation of Visual Contents from Human Brain Signals via VQA Based on Brain-Specific Attention. | Ryo Shichida, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2023 | ICASSP | Learning Graph Laplacian from Intrinsic Patterns via Gaussian Process. | Koshi Watanabe, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2023 | ICASSP | Defense Against Black-Box Adversarial Attacks Via Heterogeneous Fusion Features. | Jiahuan Zhang, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2023 | ICIP | Video-Music Retrieval with Fine-Grained Cross-Modal Alignment. | Yuki Era, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2023 | ICIP | Feature Integration via Back-Projection Ordering Multi-Modal Gaussian Process Latent Variable Model for Rating Prediction. | Kyohei Kamikawa, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2023 | ICIP | Multi-View Variational Recurrent Neural Network for Human Emotion Recognition Using Multi-Modal Biological Signals. | Yuya Moroto, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2023 | ICIP | Text-Guided Facial Image Manipulation for Wild Images via Manipulation Direction-Based Loss. | Yuto Watanabe, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2022 | ICASSP | Human Emotion Recognition Using Multi-Modal Biological Signals Based On Time Lag-Considered Correlation Maximization. | Yuya Moroto, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2022 | ICASSP | Variational Bayesian Graph Convolutional Network for Robust Collaborative Filtering. | Nozomu Onodera, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2022 | ICASSP | Distributed Label Dequantized Gaussian Process Latent Variable Model for Multi-View Data Integration. | Koshi Watanabe, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2022 | ICASSP | Generative Adversarial Network Including Referring Image Segmentation For Text-Guided Image Manipulation. | Yuto Watanabe, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2022 | ICIP | Human-Centric Image Retrieval with Gaze-Based Image Captioning. | Yuhu Feng, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2022 | ICIP | GCN-Based Multi-Modal Multi-Label Attribute Classification in Anime Illustration Using Domain-Specific Semantic Features. | Ziwen Lan, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2022 | ICIP | Gaussian Distributed Graph Constrained Multi-Modal Gaussian Process Latent Variable Model for Ordinal Labeled Data. | Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2022 | ICIP | Few-Shot Personalized Saliency Prediction with Similarity of Gaze Tendency Using Object-Based Structural Information. | Yuya Moroto, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2022 | ICIP | Assessment of Image Manipulation Using Natural Language Description: Quantification of Manipulation Direction. | Yuto Watanabe, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2022 | ICIP | Visual Sentiment Prediction Using Cross-Way Few-Shot Learning Based on Knowledge Distillation. | Yingrui Ye, Yuya Moroto, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2021 | ICASSP | Cross-Domain Semi-Supervised Deep Metric Learning for Image Sentiment Analysis. | Yun Liang, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2021 | ICASSP | Classification of Expert-Novice Level Using Eye Tracking And Motion Data via Conditional Multimodal Variational Autoencoder. | Yusuke Akamatsu, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2021 | ICASSP | Estimation of Visual Features of Viewed Image From Individual and Shared Brain Information Based on FMRI Data Using Probabilistic Generative Model. | Takaaki Higashi, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2021 | ICASSP | Feature Integration via Semi-Supervised Ordinally Multi-Modal Gaussian Process Latent Variable Model. | Kyohei Kamikawa, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2021 | ICASSP | Multi-Modal Label Dequantized Gaussian Process Latent Variable Model for Ordinal Label Estimation. | Masanao Matsumoto, Keisuke Maeda, Naoki Saito, Takahiro Ogawa, Miki Haseyama |
| 2021 | ICIP | Deep Metric Network Via Heterogeneous Semantics for Image Sentiment Analysis. | Yun Liang, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2021 | ICIP | Segmentation-Aware Text-Guided Image Manipulation. | Tomoki Haruyama, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2021 | ICIP | Cross-Domain Recommendation Method Based On Multi-Layer Graph Analysis With Visual Information. | Taisei Hirakawa, Keisuke Maeda, Takahiro Ogawa, Satoshi Asamizu, Miki Haseyama |
| 2021 | ICIP | Time-Lag Aware Multi-Modal Variational Autoencoder Using Baseball Videos And Tweets For Prediction Of Important Scenes. | Kaito Hirasawa, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2021 | ICIP | Interest Level Estimation via Multi-Modal Gaussian Process Latent Variable Factorization. | Kyohei Kamikawa, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2021 | ICIP | Few-Shot Personalized Saliency Prediction using Person Similarity based on Collaborative Multi-Output Gaussian Process Regression. | Yuya Moroto, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2021 | ICIP | Correlation-Aware Attention Branch Network Using Multi-Modal Data For Deterioration Level Estimation Of Infrastructures. | Naoki Ogawa, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2020 | ICIP | Important Scene Detection Of Baseball Videos Via Time-Lag Aware Deep Multiset Canonical Correlation Maximization. | Kaito Hirasawa, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2020 | ICIP | Feature Integration Via Geometrical Supervised Multi-View Multi-Label Canonical Correlation For Incomplete Label Assignment. | Keisuke Maeda, Sho Takahashi, Takahiro Ogawa, Miki Haseyama |
| 2019 | ICASSP | Multi-feature Fusion Based on Supervised Multi-view Multi-label Canonical Correlation Projection. | Keisuke Maeda, Sho Takahashi, Takahiro Ogawa, Miki Haseyama |
| 2019 | ICIP | Neural Network Maximizing Ordinally Supervised Multi-View Canonical Correlation for Deterioration Level Estimation. | Keisuke Maeda, Sho Takahashi, Takahiro Ogawa, Miki Haseyama |
| 2019 | ICIP | Estimation of Emotion Labels via Tensor-Based Spatiotemporal Visual Attention Analysis. | Yuya Moroto, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2018 | ICCE | Sectional Review Recommendations based on Learner's Comprehension in Video-based Learning. | Yusuke Hayashi, Keisuke Maeda, Toshio Honda, Tsukasa Hirashima |
| 2018 | ICCE | Structure-mapping Support for Learning by Analogy with Kit-Build Concept Map. | Yusuke Hayashi, Kan Yoshida, Keisuke Maeda, Akira Yamanaka, Tsukasa Hirashima |
| 2018 | ICIP | A Human-Centered Neural Network Model with Discriminative Locality Preserving Canonical Correlation Analysis for Image Classification. | Kazaha Horii, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2017 | ICIP | Automatic martian dust storm detection via decision level fusion basedondeep extreme learning machine. | Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2017 | ICIP | Automatic estimation of deterioration level on transmission towers via deep extreme learning machine based on local receptive field. | Keisuke Maeda, Sho Takahashi, Takahiro Ogawa, Miki Haseyama |
| 2016 | ICCE | Learning Task Generation from a Series of Propositions of a Learning Topic: Kit-Building Task of Concept Map and Multiple Choice Task of Fill-in-the-blank Questions. | Takuya Kitamura, Akira Yamanaka, Keisuke Maeda, Yusuke Hayashi, Tsukasa Hirashima |
| 2016 | ICCE | Comparison between Kit-Building Task of Concept Map and Multiple Choice Task of Fill-in-the-blank Question Generated from the Same Series of Propositions. | Takuya Kitamura, Akira Yamanaka, Keisuke Maeda, Yusuke Hayashi, Tsukasa Hirashima |
| 2015 | ICIP | Automatic detection of martian dust storms from heterogeneous data based on decision level fusion. | Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |