| RotationNet: Joint Object Categorization and Pose Estimation Using Multiviews from Unsupervised Viewpoints A Kanezaki, Y Matsushita, Y Nishida Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 610 | 2018 |
| Unsupervised image segmentation by backpropagation A Kanezaki 2018 IEEE international conference on acoustics, speech and signal …, 2018 | 243 | 2018 |
| Unsupervised learning of image segmentation based on differentiable feature clustering W Kim, A Kanezaki, M Tanaka IEEE Transactions on Image Processing 29, 8055-8068, 2020 | 224 | 2020 |
| Shrec16 track: largescale 3d shape retrieval from shapenet core55 M Savva, F Yu, H Su, M Aono, B Chen, D Cohen-Or, W Deng, H Su, S Bai, ... Proceedings of the eurographics workshop on 3D object retrieval 10, 13, 2016 | 214 | 2016 |
| Path planning using neural a* search R Yonetani, T Taniai, M Barekatain, M Nishimura, A Kanezaki International conference on machine learning, 12029-12039, 2021 | 84 | 2021 |
| Visual object search by learning spatial context R Druon, Y Yoshiyasu, A Kanezaki, A Watt IEEE Robotics and Automation Letters 5 (2), 1279-1286, 2020 | 72 | 2020 |
| Recognizing activities of daily living with a wrist-mounted camera K Ohnishi, A Kanehira, A Kanezaki, T Harada Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016 | 66 | 2016 |
| Large-scale 3d shape retrieval from shapenet core55: Shrec'17 track M Savva, F Yu, H Su, A Kanezaki, T Furuya, R Ohbuchi, Z Zhou, R Yu, ... Proceedings of the workshop on 3D object retrieval, 39-50, 2017 | 54 | 2017 |
| Multi-task learning using multi-modal encoder-decoder networks with shared skip connections R Kuga, A Kanezaki, M Samejima, Y Sugano, Y Matsushita Proceedings of the IEEE International Conference on Computer Vision …, 2017 | 46 | 2017 |
| Training larger networks for deep reinforcement learning K Ota, DK Jha, A Kanezaki arXiv preprint arXiv:2102.07920, 2021 | 41 | 2021 |
| Rotationnet for joint object categorization and unsupervised pose estimation from multi-view images A Kanezaki, Y Matsushita, Y Nishida IEEE transactions on pattern analysis and machine intelligence 43 (1), 269-283, 2019 | 41 | 2019 |
| Voxelized shape and color histograms for RGB-D A Kanezaki, ZC Marton, D Pangercic, T Harada, Y Kuniyoshi, M Beetz IROS Workshop on Active Semantic Perception 2, 2011 | 41 | 2011 |
| Fast object detection for robots in a cluttered indoor environment using integral 3D feature table A Kanezaki, T Suzuki, T Harada, Y Kuniyoshi 2011 IEEE International Conference on Robotics and Automation, 4026-4033, 2011 | 38 | 2011 |
| Partial matching of real textured 3D objects using color cubic higher-order local auto-correlation features A Kanezaki, T Harada, Y Kuniyoshi The Visual Computer 26, 1269-1281, 2010 | 35 | 2010 |
| Goselo: Goal-directed obstacle and self-location map for robot navigation using reactive neural networks A Kanezaki, J Nitta, Y Sasaki IEEE Robotics and Automation Letters 3 (2), 696-703, 2017 | 32 | 2017 |
| High-speed 3d object recognition using additive features in a linear subspace A Kanezaki, H Nakayama, T Harada, Y Kuniyoshi 2010 IEEE international conference on robotics and automation, 3128-3134, 2010 | 30 | 2010 |
| Clothing retrieval based on local similarity with multiple images M Mizuochi, A Kanezaki, T Harada Proceedings of the 22nd ACM international conference on Multimedia, 1165-1168, 2014 | 29 | 2014 |
| Object memory transformer for object goal navigation R Fukushima, K Ota, A Kanezaki, Y Sasaki, Y Yoshiyasu 2022 International Conference on Robotics and Automation (ICRA), 11288-11294, 2022 | 26 | 2022 |
| Efficient exploration in constrained environments with goal-oriented reference path K Ota, Y Sasaki, DK Jha, Y Yoshiyasu, A Kanezaki 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2020 | 26 | 2020 |
| SHREC’17: RGB-D to CAD retrieval with ObjectNN dataset BS Hua, QT Truong, MK Tran, QH Pham, A Kanezaki, T Lee, HY Chiang, ... Proc. Eurograph. Workshop 3D Object Retrieval, 25-32, 2017 | 19 | 2017 |
Michael BeetzIntitute for Artificial Intelligence, Computer Science Department, University of Bremen在 cs.uni-bremen.de 的电子邮件经过验证
