過去のお知らせ
IEEE Consumer Technology Society (CTSoc)のフラグシップ国際会議 2024 IEEE 13th Global Conference on Consumer Electronics (GCCE 2024)にメディアダイナミクス研究室より下記の12件の発表を行いました。また、学部4年生の登石君がExcellent Student Poster Gold Prizeを受賞しました。
[1] Tasuku Nakajima, Keisuke Maeda, Ren Togo, Takahiro Ogawa, Miki Haseyama, “Multimodal Adversarial Defense Trained on Features Extracted From Images and Brain Activity”
[2] Yuiko Uchida, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama, “An Evaluation Metric for Single Image-To-3D Models Based on a Class Confidence Score of Object Detection Models”
[3] Kenta Kubota, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama, “MLLM-Based Automatic Exploration of Editing Prompt for High Engagement Image Generation”
[4] Kenta Uesugi, Naoki Saito, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama, “Zero-Shot Composed Video Retrieval With Projection Module Bridging Modality Gap”
[5] Koshiro Toishi, Keisuke Maeda, Ren Togo, Takahiro Ogawa, Miki Haseyama, “Improving Zero-Shot Adversarial Robustness via Integrating Image Features of Foundation Models”
[6] Ren Tasai, Guang Li, Ren Togo, Minghui Tang, Takaaki Yoshimura, Hiroyuki Sugimori, Kenji Hirata, Takahiro Ogawa, Kohsuke Kudo, Miki Haseyama, “Lung Cancer Classification Using Masked Autoencoder Pretrained on J-MID Database”
[7] Jinlong Zhu, Keigo Sakurai, Ren Togo, Takahiro Ogawa, Miki Haseyama, “Structured Polyphonic Music Generation With Diffusion Transformer”
[8] Kaede Hayakawa, Keisuke Maeda, Ren Togo, Takahiro Ogawa, Miki Haseyama, “Emotion-Conditional Image Generation Reflecting Semantic Alignment With Text-To-Image Models”
[9] Longzhen Li, Guang Li, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama, “Generative Dataset Distillation Based on Large Model Pool”
[10] Ayaka Tsutsumi, Guang Li, Ren Togo, Takahiro Ogawa, Satoshi Kondo, Miki Haseyama, “Lung Disease Classification With Limited Training Data Based on Weight Selection Technique”
[11] Ryo Takahashi, Naoki Saito, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama, “Personalized Visual Emotion Classification via In-Context Learning in Multimodal LLM”
[12] Shilin Liu, Kyohei Kamikawa, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama, “Zero-Shot Controllable Music Generation From Videos Using Facial Expressions”
