知能ロボティクス・AI研究室東北大学 大学院情報科学研究科
JPEN
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COGNITIVE ROBOTICS & AI LABORATORY

Research.

研究内容

01 / RESEARCH FIELDS

主な研究項目

  • 01コンピュータビジョンComputer vision
  • 02ロボティクスRobotics
  • 03機械学習Machine learning
  • 043Dデータ認識3D data recognition

02 / PRESENTATION MATERIAL

資料

  1. 2022.09.06 第40回 日本ロボット学会学術講演会 確率ロボティクスとデータ工学ロボティクス～認識・行動学習・記号創発～ 深層学習を用いたロボットナビゲーション
  2. 2021.02.22 東京工業大学 情報理工学院 特課研説明会「金崎研究室の説明」
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  1. 2020.04.25 東京工業大学 情報理工学院 入試説明会「金崎研究室の説明」
  2. 2019.09.26 情報処理学会連続セミナー2019 第3回: AIと歩む未来(2)：画像・映像処理の最前線 「機械学習を用いた3次元データ認識について」
  3. 2018.10.30 確率場と深層学習に関する第2回CRESTシンポジウム 「深層学習を用いた三次元物体認識」
  4. 2018.08.29 「Image-to-Image Translation用GAN手法のサーベイ」
  5. 2018.05.31 第112回 ロボット工学セミナー「ロボットのための画像処理技術」 「3次元物体認識技術」
  6. 2016.06.16 第19回 知的センシングセミナー（主催 中京大学大学院情報科学研究科／企画・運営 橋本研究室） 「Kinect等の色距離センサを用いた点群処理と3D物体認識」 ※Ubuntu 16.04向け
  7. 2016.06.08 第22回 画像センシングシンポジウムチュートリアル講演会 「Kinect等の色距離センサを用いた点群処理と3D物体認識ーベーシックな手法と最新動向・ソフトウェアの紹介ー」 ※Ubuntu 14.04向け
  8. 2014.10.04 第25回 コンピュータビジョン勉強会＠関東 「RGBD画像処理と三次元物体認識」
  9. 2014.06.18 講義資料 「3D物体認識と弱教師付き学習」

03 / JOURNAL PUBLICATIONS

論文

  1. Kohei Matsumoto and Asako Kanezaki.

    EED: Embodied Environment Description through Robotic Visual Exploration.

    IEEE Robotics and Automation Letters (RA-L), 2026.
    Dataset

  2. Kei Ota, Devesh K. Jha, and Asako Kanezaki.

    A Framework for Training Larger Networks for Deep Reinforcement Learning.

    Machine Learning, Springer, 2024.
    https://doi.org/10.1007/s10994-024-06547-6

  3. Yuzhe Hao, Asako Kanezaki, Ikuro Sato, Rei Kawakami, and Koichi Shinoda.

    Egocentric Human Activities Recognition with Multi-modal Interaction Sensing.

    IEEE Sensors, 2024.

  4. Haruyuki Nakagawa and Asako Kanezaki.

    Multi-Agent Visual Coordination using Optical Wireless Communication.

    IEEE Robotics and Automation Letters (RA-L), 2023.
    https://doi.org/10.1109/LRA.2023.3304905
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  1. Hao Zheng, Qiang Zhang, and Asako Kanezaki.

    DAC: Disentanglement-and-Calibration Module for Cross-Domain Few-Shot Classification.

    IEEE Access, Vol. 11, No. 23552466, pp. 82665-82673, 2023.
    https://doi.org/10.1109/ACCESS.2023.3294984

  2. 太田佳，金崎朝子.

    動的環境下におけるロボットの動作生成.

    日本ロボット学会誌, Vol.39, No.7, pp. 581-586, 2021.

  3. Asako Kanezaki, Yasuyuki Matsushita, and Yoshifumi Nishida.

    RotationNet for Joint Object Categorization and Unsupervised Pose Estimation from Multi-view Images.

    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), Vol.43, Issue 1, pp. 269-283, 2021.
    https://doi.org/10.1109/TPAMI.2019.2922640
    Project

  4. Wonjik Kim*, Asako Kanezaki*, and Masayuki Tanaka.

    Unsupervised Learning of Image Segmentation Based on Differentiable Feature Clustering.

    IEEE Transactions on Image Processing, 2020.
    *equal contributions
    IEEE Signal Processing Society (SPS) Japan Student Journal Paper Award
    Telecom Technology Student Award
    Project

  5. Raphael Druon, Yusuke Yoshiyasu, Asako Kanezaki, and Alassane Watt.

    Visual Object Search by Learning Spatial Context.

    IEEE Robotics and Automation Letters (RA-L), Vol.5, Issue 2, pp.1279-1286, 2020. (presented in ICRA'20)
    https://doi.org/10.1109/LRA.2020.2967677

  6. Asako Kanezaki, Jirou Nitta, and Yoko Sasaki.

    GOSELO: Goal-Directed Obstacle and Self-Location Map for Robot Navigation using Reactive Neural Networks.

    IEEE Robotics and Automation Letters (RA-L), Vol.3, Issue 2, pp.696-703, 2018. (presented in ICRA'18)
    https://doi.org/10.1109/LRA.2017.2783400
    Project

  7. Nevrez Imamoglu, Wataru Shimoda, Chi Zhang, Yuming Fang, Asako Kanezaki, Keiji Yanai, and Yoshifumi Nishida.

    An Integration of Bottom-up and Top-Down Salient Cues on RGB-D Data: Saliency from Objectness vs. Non-Objectness.

    Signal, Image and Video Processing (Springer), Vol.12, Issue 2, pp.307-314, 2017.
    https://doi.org/10.1007/s11760-017-1159-7

  8. Zoltan-Csaba Marton, Ferenc Balint-Benczedi, Oscar Martinez Mozos, Nico Blodow, Asako Kanezaki, Lucian Cosmin Goron, Dejan Pangercic, and Michael Beetz.

    Part-Based Geometric Categorization and Object Reconstruction in Cluttered Table-Top Scenes.

    Journal of Intelligent & Robotic Systems, pp.35-56, 2014.
    http://dx.doi.org/10.1007/s10846-013-0011-8

  9. Asako Kanezaki, Tatsuya Harada, and Yasuo Kuniyoshi.

    Partial Matching of Real Textured 3D Objects Using Color Cubic Higher-order Local Auto-Correlation Features.

    The Visual Computer, Vol.26, No.10, pp.1269-1281, 2010.
    https://doi.org/10.1007/s00371-010-0521-3

  10. 原田達也, 金崎朝子, 國吉康夫.

    三次元環境地図からの物体探索タスク応用を目指したカラー立体高次局所自己相関特徴の開発.

    日本ロボット学会誌, Vol.27, No.7, pp.749-758, 2009.

04 / INTERNATIONAL CONFERENCES

会議発表（海外）

  1. Kaname Kitamura and Asako Kanezaki.

    Informative Viewpoint Selection for Episodic-Memory Embodied Question Answering using Omnidirectional Images.

    Asian Conference on Computer Vision (ACCV), accepted, 2026.

  2. Yuchen Che, Jingtu Wu, Hao Zheng, and Asako Kanezaki.

    COG: Confidence-aware Optimal Geometric Correspondence for Unsupervised Single-reference Novel Object Pose Estimation.

    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), accepted, 2026.
    Paper Code

  3. Masaru Yajima, Yuma Shin, Rei Kawakami, Asako Kanezaki, and Kei Ota.

    Touch2Insert: Zero-Shot Peg Insertion by Touching Intersections of Peg and Hole.

    IEEE International Conference on Robotics and Automation (ICRA), accepted, 2026.

  4. Haru Kondoh and Asako Kanezaki.

    Embodied Navigation with Auxiliary Task of Action Description Prediction.

    IEEE/CVF International Conference on Computer Vision (ICCV), 2025.
    Paper Code

  5. Masaru Yajima, Kei Ota, Asako Kanezaki, and Rei Kawakami.

    Zero-Shot Peg Insertion: Identifying Mating Holes and Estimating SE(2) Poses with Vision-Language Models.

    IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2025.
    Paper
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  1. Kuanting Wu, Kei Ota, and Asako Kanezaki.

    FlowLoss: Dynamic Flow-Conditioned Loss Strategy for Video Diffusion Models.

    The 19th International Conference on Machine Vision Applications (MVA), 2025.
    Paper

  2. Jiawei Jiang, Kei Ota, Devesh K. Jha, and Asako Kanezaki.

    Modality Selection and Skill Segmentation via Cross-Modality Attention.

    The 19th International Conference on Machine Vision Applications (MVA), 2025.
    Paper

  3. Kohei Matsumoto and Asako Kanezaki.

    EED: Embodied Environment Description through Robotic Visual Exploration.

    The 6th Embodied AI workshop at CVPR, 2025.
    Dataset

  4. Yuchen Che, Ryo Furukawa, and Asako Kanezaki.

    OP-Align: Object-level and Part-level Alignment for Self-supervised Category-level Articulated Object Pose Estimation.

    The 18th European Conference on Computer Vision (ECCV), (oral), 2024.
    Paper Code

  5. Yunyi Guan and Asako Kanezaki.

    Active Object Recognition with Trained Multi-view Based 3D Object Recognition Network.

    2nd IEEE International Conference on Robotics and Automation (ICRA) Workshop on Mobile Manipulation and Embodied Intelligence, 2024.
    Paper

  6. Carlos Gutierrez-Alvarez, Rafael Flor-Rodr&iacuteguez-Rabad&aacuten, Asako Kanezaki, and Roberto Javier L&oacutepez-Sastre.

    OffNav: Offline Reinforcement Learning for Visual Semantic Navigation.

    IEEE International Conference on Robotics and Automation (ICRA) Workshop on Human-aligned Reinforcement Learning for Autonomous Agents and Robots, 2024.
    Paper

  7. Kei Ota, Devesh Jha, Krishna Murthy Jatavallabhula, Asako Kanezaki, and Joshua B. Tenenbaum.

    Tactile Estimation of Extrinsic Contact Patch for Stable Placement.

    IEEE International Conference on Robotics and Automation (ICRA), 2024.
    Paper

  8. Haruyuki Nakagawa, Yoshitaka Miyatani, and Asako Kanezaki.

    Linking Vision and Multi-Agent Communication through Visible Light Communication using Event Cameras.

    Int. Joint Conf. on Autonomous Agents & Multiagent Systems (AAMAS), 2024.
    Paper

  9. Haru Kondoh and Asako Kanezaki.

    Multi-goal Audio-visual Navigation using Sound Direction Map.

    IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2023.
    Paper

  10. Nanami Kotani and Asako Kanezaki.

    Point Anywhere: Directed Object Estimation from Omnidirectional Images.

    Special Interest Group on Computer Graphics and Interactive Techniques Conference Posters (SIGGRAPH '23 Posters), 2023.
    Paper Dataset

  11. Wenru Zheng, Ryota Yoshihashi, Rei Kawakami, Ikuro Sato, and Asako Kanezaki.

    Multi Event Localization by Audio-Visual Fusion with Omnidirectional Camera and Microphone Array.

    6th CVPR Workshop on Multimodal Learning and Applications (MULA), 2023.
    Dataset

  12. Hao Zheng, Runqi Wang, Jianzhuang Liu, and Asako Kanezaki.

    Cross-Level Distillation and Feature Denoising for Cross-Domain Few-Shot Classification.

    International Conference on Learning Representations (ICLR), 2023.
    Paper Code

  13. Kei Ota, Hsiao-Yu Tung, Kevin A. Smith, Anoop Cherian, Tim K. Marks, Alan Sullivan, Asako Kanezaki, and Joshua B. Tenenbaum.

    H-SAUR: Hypothesize, Simulate, Act, Update, and Repeat for Understanding Object Articulations from Interactions.

    IEEE International Conference on Robotics and Automation (ICRA), 2023.
    Paper

  14. Yuzhe Hao, Kuniaki Uto, Asako Kanezaki, Ikuro Sato, Rei Kawakami, and Koichi Shinoda.

    EvIs-Kitchen: Egocentric Human Activities Recognition with Video and Inertial Sensor data.

    Multimedia Modeling (MMM), 2023.

  15. Hana Hoshino, Kei Ota, Asako Kanezaki, and Rio Yokota.

    OPIRL: Sample Efficient Off-Policy Inverse Reinforcement Learning via Distribution Matching.

    IEEE International Conference on Robotics and Automation (ICRA), 2022.
    Paper Code

  16. Rui Fukushima, Kei Ota, Asako Kanezaki, Yoko Sasaki, and Yusuke Yoshiyasu.

    Object Memory Transformer for Object Goal Navigation.

    IEEE International Conference on Robotics and Automation (ICRA), 2022.
    Paper Code

  17. Takashi Konno, Ayako Amma, and Asako Kanezaki.

    Incremental Multi-view Object Detection from a Moving Camera.

    ACM Multimedia Asia (ACMMMA), 2020.
    Project

  18. Kei Ota, Devesh K. Jha, Tadashi Onishi, Asako Kanezaki, Yusuke Yoshiyasu, Yoko Sasaki, Toshisada Mariyama, Daniel Nikovski.

    Deep Reactive Planning in Dynamic Environments.

    The Conference on Robot Learning (CoRL), 2020.
    PDF YouTube

  19. Kei Ota, Yoko Sasaki, Devesh K. Jha, Yusuke Yoshiyasu, and Asako Kanezaki.

    Efficient Exploration in Constrained Environments with Goal-Oriented Reference Path.

    IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2020), 2020.
    PDF

  20. Yoko Sasaki, Syusuke Matsuo, Asako Kanezaki, and Hiroshi Takemura.

    A3C Based Motion Learning for an Autonomous Mobile Robot in Crowds.

    IEEE International Conference on System Man and Cybernetics (SMC2019), pp.1046-1052, 2019.

  21. Nevrez Imamoglu, Guanqun Ding, Yuming Fang, Asako Kanezaki, Toru Kouyama, and Ryosuke Nakamura.

    Salient object detection on hyperspectral images using features learned from unsupervised segmentation task.

    IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.2192-2196, 2019.
    PDF

  22. Asako Kanezaki, Yasuyuki Matsushita, and Yoshifumi Nishida.

    RotationNet: Joint Object Categorization and Pose Estimation Using Multiviews from Unsupervised Viewpoints.

    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.5010-5019, 2018.
    Project

  23. Asako Kanezaki.

    Unsupervised Image Segmentation by Backpropagation.

    IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.1543-1547, 2018.
    Project

  24. Mikiko Oono, Yoshifumi Nishida, Koji Kitamura, Asako Kanezaki, and Tatsuhiro Yamanaka.

    "Change the changeable" framework for implementation research in health.

    the 10th International Conference on Computer Supported Education (CSEDU), (oral), 2017.

  25. Ryohei Kuga, Asako Kanezaki, Masaki Samejima, Yusuke Sugano, and Yasuyuki Matsushita.

    Multi-modal U-Nets for Multi-task Scene Understanding.

    IEEE/ISPRS 4th Joint Workshop on Multi-Sensor Fusion for Dynamic Scene Understanding, pp.403-411, (oral), 2017.
    PDF

  26. Manolis Savva, Fisher Yu, Hao Su, Asako Kanezaki, Takahiko Furuya, Ryutarou Ohbuchi, Zhichao Zhou, Rui Yu, Song Bai, Xiang Bai, Masaki Aono, Atsushi Tatsuma, S. Thermos, A. Axenopoulos, G. Th. Papadopoulos, P. Daras, Xiao Deng, Zhouhui Lian, Bo Li, Henry Johan, Yijuan Lu, and Sanjeev Mk.

    SHREC'17 Track: Large-Scale 3D Shape Retrieval from ShapeNet Core55.

    Eurographics Workshop on 3D Object Retrieval 2017, 2017.
    PDF

  27. Binh-Son Hua, Quang-Trung Truong, Minh-Khoi Tran, Quang-Hieu Pham, Asako Kanezaki, Tang Lee, HungYueh Chiang, Winston Hsu, Bo Li, Yijuan Lu, Henry Johan, Shoki Tashiro, Masaki Aono, Minh-Triet Tran, Viet-Khoi Pham, Hai-Dang Nguyen, Vinh-Tiep Nguyen, Quang-Thang Tran, Thuyen V. Phan, Bao Truong, Minh N. Do, Anh-Duc Duong, Lap-Fai Yu, Duc Thanh Nguyen, and Sai-Kit Yeung.

    SHREC'17: RGB-D to CAD Retrieval with ObjectNN Dataset.

    Eurographics Workshop on 3D Object Retrieval 2017, 2017.
    PDF

  28. Tomoaki Saito, Asako Kanezaki, and Tatsuya Harada.

    IBC127: Video Dataset for Fine-grained Bird Classification.

    IEEE International Conference on Multimedia & Expo (ICME), 2016.
    Dataset

  29. Katsunori Ohnishi, Atsushi Kanehira, Asako Kanezaki, and Tatsuya Harada.

    Recognizing Activities of Daily Living with a Wrist-mounted Camera.

    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), (spotlight), 2016.
    Project

  30. Chie Kamada, Asako Kanezaki, and Tatsuya Harada.

    Probabilistic Semi-Canonical Correlation Analysis.

    the 23rd Annual ACM International Conference on Multimedia (ACMMM 2015), pp.1131-1134, 2015.

  31. Asako Kanezaki and Tatsuya Harada.

    3D Selective Search for Obtaining Object Candidates.

    IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2015), pp.82-87, 2015.
    PDF code

  32. Asako Kanezaki, Emanuele Rodolà, Daniel Cremers, and Tatsuya Harada.

    Learning Similarities for Rigid and Non-Rigid Object Detection.

    International Conference on 3D Vision (3DV 2014), pp.720-727, 2014.
    PDF

  33. Sho Inaba, Asako Kanezaki, and Tatsuya Harada.

    Automatic Image Synthesis from Keywords Using Scene Context.

    the 22nd Annual ACM International Conference on Multimedia (ACMMM 2014), pp.1149-1152, 2014.

  34. Masaru Mizuochi, Asako Kanezaki, and Tatsuya Harada.

    Clothing Retrieval Based on Local Similarity with Multiple Images.

    the 22nd Annual ACM International Conference on Multimedia (ACMMM 2014), pp.1165-1168, 2014.

  35. Asako Kanezaki, Yusuke Mukuta, and Tatsuya Harada.

    Mirror Reflection Invariant HOG descriptors for Object Detection.

    IEEE 21st International Conference on Image Processing (ICIP 2014), pp.1594-1598, 2014.
    PDF

  36. Asako Kanezaki, Sho Inaba, Yoshitaka Ushiku, Yuya Yamashita, Hiroshi Muraoka, Yasuo Kuniyoshi, and Tatsuya Harada.

    Hard Negative Classes for Multiple Object Detection.

    IEEE International Conference on Robotics and Automation (ICRA 2014), pp.3066-3073, 2014.
    PDF

  37. Asako Kanezaki, Yasuo Kuniyoshi, and Tatsuya Harada.

    Weakly-supervised Multi-class Object Detection Using Multi-type 3D Features.

    the 21st Annual ACM International Conference on Multimedia (ACMMM 2013), pp.605-608, 2013.
    PDF Dataset

  38. Asako Kanezaki, Tatsuya Harada, and Yasuo Kuniyoshi.

    Scale and Rotation Invariant Color Features for Weakly-Supervised Object Learning in 3D Space.

    IEEE ICCV Workshop on 3D Representation and Recognition (3dRR-11), 2011.
    PDF

  39. Asako Kanezaki, Zoltan-Csaba Marton, Dejan Pangercic, Tatsuya Harada, Yasuo Kuniyoshi, and Michael Beetz.

    Voxelized Shape and Color Histograms for RGB-D.

    IEEE IROS Workshop on Active Semantic Perception and Object Search in the Real World (ASP-AVS-11), 2011.
    PDF

  40. Asako Kanezaki, Takahiro Suzuki, Tatsuya Harada, and Yasuo Kuniyoshi.

    Fast Object Detection for Robots in a Cluttered Indoor Environment Using Integral 3D Feature Table.

    IEEE International Conference on Robotics and Automation (ICRA 2011), pp.4026-4033, 2011.
    PDF

  41. Asako Kanezaki, Hideki Nakayama, Tatsuya Harada, and Yasuo Kuniyoshi.

    High-speed 3D Object Recognition Using Additive Features in A linear Subspace.

    2010 IEEE International Conference on Robotics and Automation (ICRA 2010), pp.3128-3134, 2010.
    2010 IEEE Robotics and Automation Society Japan Chapter Young Award (ICRA 2010)
    PDF

  42. Asako Kanezaki, Tatsuya Harada, and Yasuo Kuniyoshi.

    Partial Matching for Real Textured 3D Objects using Color Cubic Higher-order Local Auto-Correlation Features.

    Eurographics Workshop on 3D Object Retrieval 2009, pp.9-12, 2009.

05 / DOMESTIC CONFERENCES

会議発表（国内）

  1. 中村 遼平，中川 遥之，宮谷 佳孝，金崎 朝子.

    可視光通信による自己位置推定を想定したマルチエージェント協調システム

    Meeting on Image Recognition and Understandings (MIRU), (oral), 2026.

  2. 伊藤 誠治，矢島 優，太田 佳，金崎 朝子.

    教師なしスキル分解による長期ロボットタスク模倣学習

    Meeting on Image Recognition and Understandings (MIRU), (oral), 2026.

  3. 南里 絢花，Klara Reichard，Mert Kıray，Benjamin Busam，Federico Tombari，金崎 朝子.

    視点依存の関係性を用いた3Dセグメンテーション

    Meeting on Image Recognition and Understandings (MIRU), (oral), 2026.

  4. 相澤 航輝，中西 康輔，安井 裕司，金崎 朝子.

    逆強化学習とモデルベース経路計画による安全なロボットナビゲーション

    Meeting on Image Recognition and Understandings (MIRU), 2026.

  5. 近藤 暖，太田 佳，金崎 朝子，Yueh-Hua Wu.

    視覚言語行動モデルのための反実仮想的教師信号を用いたオフライン強化学習

    Meeting on Image Recognition and Understandings (MIRU), 2026.

  6. 北村 要，金崎 朝子.

    全天球画像を用いたOpen-Vocabulary EQAにおける重要視点選択

    Meeting on Image Recognition and Understandings (MIRU), (oral), 2026.

  7. 小島 悠介，相澤 航輝，金崎 朝子.

    自動運転のための解釈可能な逆強化学習手法

    Meeting on Image Recognition and Understandings (MIRU), 2026.

  8. 近藤 暖，小津野 将，金崎 朝子，田中 一敏.

    接触を伴う多様な物体操作学習のための直列弾性アクチュエータアームの剛性設計

    Meeting on Image Recognition and Understandings (MIRU), 2026.

  9. 中村 遼平，金崎 朝子.

    可視光通信による自己位置推定を想定した三次元再構成のためのマルチエージェント協調システム

    The 43th Annual Conference of the Robotics Society of Japan (RSJ), 1C2-05, 2025.

  10. 矢島 優，川上 玲，金崎 朝子，太田 佳.

    触覚センサを用いた高精度な姿勢推定によるゼロショットでのコネクタ挿入

    The 43th Annual Conference of the Robotics Society of Japan (RSJ), 1L4-04, 2025.

  11. 長谷川 凌大，太田 佳，金崎 朝子.

    ロボットとのインタラクションを用いた関節付き物体の状態推定

    The 43th Annual Conference of the Robotics Society of Japan (RSJ), 2C2-01, 2025.

  12. 伊藤 誠治，太田 佳，蔣 嘉瑋，金崎 朝子.

    マルチモーダル観測に基づくロボット動作の教師なしスキル分割

    The 43th Annual Conference of the Robotics Society of Japan (RSJ), 2C2-02, 2025.
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  1. 近藤 暖，金崎 朝子.

    DescRLを用いた実世界意味的視聴覚ナビゲーション

    The 43th Annual Conference of the Robotics Society of Japan (RSJ), 3E1-01, 2025.

  2. 武田 康司，金崎 朝子.

    質問生成器を用いた物体ゴールナビゲーション手法の開発

    The 43th Annual Conference of the Robotics Society of Japan (RSJ), 3E1-03, 2025.

  3. 近藤 暖，金崎 朝子.

    説明文生成を補助タスクとする意味的視聴覚ナビゲーション

    Meeting on Image Recognition and Understandings (MIRU), OS-1E-08, 2024.
    MIRU学生優秀賞

  4. 齊藤 温人，金崎 朝子.

    オープンセット認識におけるクラス間の類似度に基づく学習クラス選択

    Meeting on Image Recognition and Understandings (MIRU), IS-1-086, 2024.

  5. 中村 遼平，金崎 朝子.

    単一画像からの関節付き物体の新規視点画像生成

    Meeting on Image Recognition and Understandings (MIRU), IS-1-109, 2024.

  6. 太田 朔哉，金崎 朝子.

    テキスト付き動画データを用いた動作生成に関する研究

    Meeting on Image Recognition and Understandings (MIRU), IS-3-083, 2024.

  7. 小谷 七海，金崎 朝子.

    注目領域の抽出に基づく全天球画像からの指示物体推定

    Meeting on Image Recognition and Understandings (MIRU), IS2-66, 2023.

  8. 合楽 慧，金崎 朝子.

    画像の意味的領域分割を用いた強化学習による室内環境探索

    Meeting on Image Recognition and Understandings (MIRU), IS2-109, 2023.

  9. 近藤 暖，金崎 朝子.

    動的複数音源定位手法を用いたマルチゴール視聴覚ナビゲーション

    Meeting on Image Recognition and Understandings (MIRU), IS3-109, 2023.

  10. Yunyi Guan and Asako Kanezaki.

    Active Object Recognition in Discrete and Continuous View Settings

    Meeting on Image Recognition and Understandings (MIRU), IS1-111, 2023.

  11. 神山 慶伍，太田 佳，高波 亮介，金崎 朝子.

    強化学習エージェントの軌跡を用いたサンプルベース経路計画

    Pattern Recognition and Media Understanding (PRMU), pp. 1-6, 2022.

  12. 中川 遥之，金崎 朝子.

    光無線通信を用いたマルチエージェント強化学習

    Meeting on Image Recognition and Understandings (MIRU), IS1-37, 2022.

  13. 熊坂 雅之，金崎 朝子.

    セグメンテーション画像を入力としたシーン分類手法の検討

    Meeting on Image Recognition and Understandings (MIRU), IS2-32, 2022.

  14. 北山 翼，川上 玲，佐藤 育郎，吉橋 亮太，金崎 朝子.

    球面畳み込みの時間軸拡張による全天球映像からの行動種別の領域分割

    Meeting on Image Recognition and Understandings (MIRU), IS1-68, 2022.

  15. Wenru Zheng, Rei Kawakami, Ikuro Sato, Ryota Yoshihashi, and Asako Kanezaki.

    Event Recognition by Audio-Visual Fusion with Omnidirectional Camera and Microphone Array

    Meeting on Image Recognition and Understandings (MIRU), IS2-65, 2022.

  16. 加納諒也，和田一義，金崎朝子，冨沢哲雄，谷川民生.

    深層学習による物体認識のためのマーカの検討 ～第一報：AlexNetによる認識率の比較～

    日本機械学会ロボティクス・メカトロニクス講演会, 2019.

  17. 佐々木洋子，松尾修佑，金崎朝子，竹村裕.

    歩行者観測履歴を用いた深層強化学習による車輪ロボットの雑踏切り抜け動作生成

    日本機械学会ロボティクス・メカトロニクス講演会, 2019.

  18. 佐々木 洋子，坂東 宜昭，金崎 朝子.

    科学館での自律移動ロボット実証実験 ～ロボットは人混みで音を聞き分けられるか!?～

    第52回人工知能学会 AI チャレンジ研究会, 2018.

  19. 渋谷 薫, 金崎 朝子, 大西 正輝.

    深層学習による画像識別問題に帰着した人の流れのシミュレーション

    Meeting on Image Recognition and Understandings (MIRU), 2018.

  20. 金崎 朝子, 松下 康之, 西田 佳史.

    視点教示なし多視点画像深層学習による物体のカテゴリ・姿勢同時推定

    第24回 画像センシングシンポジウム (SSII), 2018.

  21. 藤橋 一輝, 木村 雅之, 金崎 朝子, 小澤 順.

    半教師あり学習による商品画像中の個数と位置の同時推定

    第32回 人工知能学会全国大会 (JSAI), 2018.

  22. 鈴木 亮太, QIU YUE, 金崎 朝子, 岩田 健司, 佐藤 雄隆.

    物体認識技術を活用したインタラクティブVR空間の構成

    第23回 画像センシングシンポジウム (SSII), 2017.

  23. 西田 佳史, 北村 光司, 佐々木 洋子, 金崎 朝子, Shi Boxin, 大野 美喜子, 楠本 欣司.

    繋げる人工知能 ：生活機能レジリエント社会のための スマートリビングネットを用いた生活知能研究

    第17回 SICEシステムインテグレーション部門講演会, 2016.

  24. 金崎 朝子.

    三次元情報を活用した物体検出の三手法

    Vision Enginieering Workshop (ViEW), OS5-01, pp.284-287, 2015.

  25. 金崎 朝子, Emanuele Rodolà, 原田 達也.

    グラフマッチング学習を用いたRGB-D画像からの物体検出

    第20回 ロボティクスシンポジア, pp.432-437, 2015.

  26. 金崎 朝子, Emanuele Rodolà, Daniel Cremers, 原田 達也.

    対応点集合類似度学習を用いた剛体・非剛体物体検出

    Pattern Recognition and Media Understanding (PRMU), pp.13-18, 2014.

  27. 金崎 朝子, Emanuele Rodolà, 原田 達也.

    RGB-D画像からの物体検出における対応点集合類似度の学習

    the 32th Annual Conference of the Robotics Society of Japan (RSJ), 3I2-03, 2014.
    2015 研究奨励賞．第30回 日本ロボット学会 学術講演会（RSJ）

  28. 金崎 朝子, 稲葉 翔, 牛久 祥孝, 山下 裕也, 村岡 宏是, 原田 達也, 國吉 康夫.

    大規模画像データセットを用いたマルチクラス物体検出器の同時学習 〜物体毎に特化した負例クラスの導入〜

    Pattern Recognition and Media Understanding (PRMU), pp.105-112, 2012.
    2012 研究奨励賞. 電子情報通信学会パターン認識・マルチメディア理解研究会 (PRMU)

  29. 金崎 朝子, 原田 達也, 國吉 康夫.

    多種類の三次元特徴量を用いた物体セグメンテーションの弱教師付き学習

    Meeting on Image Recognition and Understandings (MIRU), OS14-03, 2012.

  30. 稲葉 翔, 村岡 宏是, 山下 裕也, 牛久 祥孝, 金崎 朝子, 原田 達也, 國吉 康夫.

    学習時間に着目した効率的な大規模画像分類

    Meeting on Image Recognition and Understandings (MIRU), OS6-03, 2012.

  31. 金崎 朝子, 原田 達也, 國吉 康夫.

    カラー三次元積分特徴と線形部分空間法による実世界からの高速物体検出

    Meeting on Image Recognition and Understandings (MIRU), IS1-59, pp.448-455, 2010.

  32. 金崎 朝子, 原田 達也, 國吉 康夫.

    積分特徴と部分空間法を用いた高速三次元物体認識の実データへの適用

    Pattern Recognition and Media Understanding (PRMU), pp.207-212, 2009.

  33. 金崎 朝子, 中山 英樹, 原田 達也, 國吉 康夫.

    部分空間法とカラー立体高次局所自己相関特徴を用いた高速三次元物体認識

    Meeting on Image Recognition and Understandings (MIRU), OS4-3:103-OS4-3:110, 2009.

  34. 金崎 朝子, 原田 達也, 國吉 康夫.

    三次元環境地図からの物体探索タスク応用を目指したカラー立体高次局所自己相関特徴の開発

    the 26th Annual Conference of the Robotics Society of Japan (RSJ), 1L3-06, 2008.