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ORCIDTeppei Suzuki
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2020 – today
- 2024
[j2]Teppei Suzuki
, Takashi Hasebe, Tsubasa Miyazaki:
Quantum support vector machines for classification and regression on a trapped-ion quantum computer. Quantum Mach. Intell. 6(1): 31 (2024)- [i14]Teppei Suzuki:
Fed3DGS: Scalable 3D Gaussian Splatting with Federated Learning. CoRR abs/2403.11460 (2024) - 2023
- [j1]Yoshiaki Kataoka, Yuki Saito, Ryo Takeda, Tomoya Ishida, Shigeru Tadano, Teppei Suzuki, Kentaro Nakamura, Akimi Nakata, Satoshi Osuka, Satoshi Yamada, Mina Samukawa, Harukazu Tohyama:
Evaluation of Lower-Limb Kinematics during Timed Up and Go (TUG) Test in Subjects with Locomotive Syndrome (LS) Using Wearable Gait Sensors (H-Gait System). Sensors 23(2): 687 (2023) - [i13]Teppei Suzuki:
Federated Learning for Large-Scale Scene Modeling with Neural Radiance Fields. CoRR abs/2309.06030 (2023) - 2022
- [c18]Hiroaki Igarashi, Kenichi Yoneji, Kohta Ishikawa, Rei Kawakami, Teppei Suzuki, Shingo Yashima, Ikuro Sato:
Multi-task Curriculum Learning based on Gradient Similarity. BMVC 2022: 705 - [c17]Teppei Suzuki:
TeachAugment: Data Augmentation Optimization Using Teacher Knowledge. CVPR 2022: 10894-10904 - [c16]Shingo Yashima, Teppei Suzuki, Kohta Ishikawa, Ikuro Sato, Rei Kawakami:
Feature Space Particle Inference for Neural Network Ensembles. ICML 2022: 25452-25468 - [i12]Teppei Suzuki:
TeachAugment: Data Augmentation Optimization Using Teacher Knowledge. CoRR abs/2202.12513 (2022) - [i11]Teppei Suzuki:
Clustering as Attention: Unified Image Segmentation with Hierarchical Clustering. CoRR abs/2205.09949 (2022) - [i10]Shingo Yashima, Teppei Suzuki, Kohta Ishikawa, Ikuro Sato, Rei Kawakami:
Feature Space Particle Inference for Neural Network Ensembles. CoRR abs/2206.00944 (2022) - 2021
- [c15]Ikuro Sato, Guoqing Liu, Kohta Ishikawa, Teppei Suzuki, Masayuki Tanaka:
Does End-to-End Trained Deep Model Always Perform Better than Non-End-to-End Counterpart? Image Processing: Algorithms and Systems 2021 - [i9]Teppei Suzuki:
Implicit Integration of Superpixel Segmentation into Fully Convolutional Networks. CoRR abs/2103.03435 (2021) - 2020
- [c14]Teppei Suzuki, Keisuke Ozawa, Yusuke Sekikawa:
Rethinking PointNet Embedding for Faster and Compact Model. 3DV 2020: 791-800 - [c13]Teppei Suzuki, Ikuro Sato:
Adversarial Transformations for Semi-Supervised Learning. AAAI 2020: 5916-5923 - [c12]Teppei Suzuki:
Superpixel Segmentation Via Convolutional Neural Networks with Regularized Information Maximization. ICASSP 2020: 2573-2577 - [c11]Yuta Kawachi, Teppei Suzuki:
Unsupervised Auto-Encoding Multiple-Object Tracker for Constraint-Consistent Combinatorial Problem. ICASSP 2020: 6054-6058 - [c10]Hirokatsu Kataoka, Teppei Suzuki, Kodai Nakashima, Yutaka Satoh, Yoshimitsu Aoki:
Joint Pedestrian Detection and Risk-level Prediction with Motion-Representation-by-Detection. ICRA 2020: 1021-1027 - [c9]Jun Nagata, Yusuke Sekikawa, Kosuke Hara, Teppei Suzuki, Yoshimitsu Aoki:
QR-code Reconstruction from Event Data via Optimization in Code Subspace. WACV 2020: 2113-2121 - [i8]Teppei Suzuki:
Superpixel Segmentation via Convolutional Neural Networks with Regularized Information Maximization. CoRR abs/2002.06765 (2020) - [i7]Teppei Suzuki, Keisuke Ozawa, Yusuke Sekikawa:
Rethinking PointNet Embedding for Faster and Compact Model. CoRR abs/2007.15855 (2020) - [i6]Yusuke Sekikawa, Teppei Suzuki:
Irregularly Tabulated MLP for Fast Point Feature Embedding. CoRR abs/2011.09852 (2020)
2010 – 2019
- 2019
- [c8]Teppei Suzuki, Ikuro Sato:
A New Way of Estimating Distances to Foregoing Vehicles from a Monocular Camera with Error Modeling. IV 2019: 2208-2214 - [i5]Teppei Suzuki, Ikuro Sato:
Adversarial Transformations for Semi-Supervised Learning. CoRR abs/1911.06181 (2019) - [i4]Yusuke Sekikawa, Teppei Suzuki:
Tabulated MLP for Fast Point Feature Embedding. CoRR abs/1912.00790 (2019) - 2018
- [c7]Kaori Abe, Munetaka Minoguchi, Teppei Suzuki, Tomoyuki Suzuki, Naofumi Akimoto, Yue Qiu, Ryota Suzuki, Kenji Iwata, Yutaka Satoh, Hirokatsu Kataoka:
Fashion Culture Database: Construction of Database for World-wide Fashion Analysis. ICARCV 2018: 1721-1726 - [c6]Teppei Suzuki, Shuichi Akizuki, Naoki Kato, Yoshimitsu Aoki:
Superpixel Convolution for Segmentation. ICIP 2018: 3249-3253 - [c5]Hirokatsu Kataoka, Teppei Suzuki, Shoko Oikawa, Yasuhiro Matsui, Yutaka Satoh:
Drive Video Analysis for the Detection of Traffic Near-Miss Incidents. ICRA 2018: 1-8 - [i3]Hirokatsu Kataoka, Teppei Suzuki, Shoko Oikawa, Yasuhiro Matsui, Yutaka Satoh:
Drive Video Analysis for the Detection of Traffic Near-Miss Incidents. CoRR abs/1804.02555 (2018) - 2017
- [c4]Kyohei Otsuka, Kosuke Hara, Teppei Suzuki, Yoshimitsu Aoki:
Danger level modeling and analysis of vehicle-pedestrian encounter using situation dependent topic model. Intelligent Vehicles Symposium 2017: 251-256 - [c3]Katsuhiko Ogasawara, Satoshi Kaga, Teppei Suzuki, Yuji Tani, Fumihiro Higashikawa, Hisashi Enomoto, Hiroyuki Moriyama, Nobuyuki Kise:
Willingness to Pay for Elderly Tele-Care System Using Digital Terrestrial Broadcasting. MedInfo 2017: 1366 - [c2]Teppei Suzuki, Yoshimitsu Aoki, Hirokatsu Kataoka:
Pedestrian near-miss analysis on vehicle-mounted driving recorders. MVA 2017: 416-419 - [i2]Kaori Abe, Teppei Suzuki, Shunya Ueta, Akio Nakamura, Yutaka Satoh, Hirokatsu Kataoka:
Changing Fashion Cultures. CoRR abs/1703.07920 (2017) - [i1]Hirokatsu Kataoka, Soma Shirakabe, Yun He, Shunya Ueta, Teppei Suzuki, Kaori Abe, Asako Kanezaki, Shinichiro Morita, Toshiyuki Yabe, Yoshihiro Kanehara, Hiroya Yatsuyanagi, Shinya Maruyama, Ryousuke Takasawa, Masataka Fuchida, Yudai Miyashita, Kazushige Okayasu, Yuta Matsuzaki:
cvpaper.challenge in 2016: Futuristic Computer Vision through 1, 600 Papers Survey. CoRR abs/1707.06436 (2017) - 2016
- [c1]Shota Takayama, Teppei Suzuki, Yoshimitsu Aoki, Sho Isobe, Makoto Masuda:
Tracking People in Dense Crowds Using Supervoxels. SITIS 2016: 532-537
Coauthor Index
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