Determination of All Tessellation Polyhedra with Regular Polygonal Faces. - Jin Akiyama; Takayasu Kuwata; Stefan Langerman; Kenji Okawa; Ikuro Sato; Geoffrey C. Shephard (CGGA, 2010)

Crossing obstacle detection with a vehicle-mounted camera. - Ikuro Sato; Chiharu Yamano; Hirohiko Yanagawa (Intelligent Vehicles Symposium, 2011)

On Reversibility among Parallelohedra. - Jin Akiyama; Ikuro Sato; Hyunwoo Seong (EGC, 2011)

Tessellabilities, Reversibilities, and Decomposabilities of Polytopes - (A Survey). - Jin Akiyama; Ikuro Sato; Hyunwoo Seong (GSI, 2013)

Sparse Isotropic Hashing. - Ikuro Sato; Mitsuru Ambai; Koichiro Suzuki (IPSJ Trans. Comput. Vis. Appl., 2013)

Distance Computation Between Binary Code and Real Vector for Efficient Keypoint Matching. - Yuji Yamauchi; Mitsuru Ambai; Ikuro Sato; Yuichi Yoshida; Hironobu Fujiyoshi (IPSJ Trans. Comput. Vis. Appl., 2013)

Asymmetric Feature Representation for Object Recognition in Client Server System. - Yuji Yamauchi; Mitsuru Ambai; Ikuro Sato; Yuichi Yoshida; Hironobu Fujiyoshi; Takayoshi Yamashita (ACCV (1), 2014)

SPADE: Scalar Product Accelerator by Integer Decomposition for Object Detection. - Mitsuru Ambai; Ikuro Sato (ECCV (5), 2014)

Pairwise Rotation Hashing for High-dimensional Features. - Kohta Ishikawa; Ikuro Sato; Mitsuru Ambai (CoRR, 2015)

APAC: Augmented PAttern Classification with Neural Networks. - Ikuro Sato; Hiroki Nishimura; Kensuke Yokoi (CoRR, 2015)

Predicting statistics of asynchronous SGD parameters for a large-scale distributed deep learning system on GPU supercomputers. - Yosuke Oyama; Akihiro Nomura 002; Ikuro Sato; Hiroki Nishimura; Yukimasa Tamatsu; Satoshi Matsuoka (IEEE BigData, 2016)

Fast Eigen Matching. - Yusuke Sekikawa; Koichiro Suzuki; Yuichi Yoshida; Kosuke Hara; Ikuro Sato (BMVC, 2016)

Binary-Decomposed DCNN for Accelerating Computation and Compressing Model Without Retraining. - Ryuji Kamiya; Takayoshi Yamashita; Mitsuru Ambai; Ikuro Sato; Yuji Yamauchi; Hironobu Fujiyoshi (ICCV Workshops, 2017)

Asynchronous, Data-Parallel Deep Convolutional Neural Network Training with Linear Prediction Model for Parameter Transition. - Ikuro Sato; Ryo Fujisaki; Yosuke Oyama; Akihiro Nomura 002; Satoshi Matsuoka (ICONIP (2), 2017)

A recursive Algorithm for the k-face Numbers of Wythoffian-n-polytopes Constructed from Regular Polytopes. - Jin Akiyama; Sin Hitotumatu; Motonaga Ishii; Akihiro Matsuura; Ikuro Sato; Shun Toyoshima (J. Inf. Process., 2017)

Constant Velocity 3D Convolution. - Yusuke Sekikawa; Kohta Ishikawa; Kosuke Hara; Yuichi Yoshida; Koichiro Suzuki; Ikuro Sato; Hideo Saito 001 (3DV, 2018)

Learning-Based Multiple-Path Prediction for Early Warning. - Ikuro Sato; Guoqing Liu (Intelligent Vehicles Symposium, 2018)

Canonical and Compact Point Cloud Representation for Shape Classification. - Kent Fujiwara; Ikuro Sato; Mitsuru Ambai; Yuichi Yoshida; Yoshiaki Sakakura (CoRR, 2018)

Towards Human-Friendly Referring Expression Generation. - Mikihiro Tanaka; Takayuki Itamochi; Kenichi Narioka; Ikuro Sato; Yoshitaka Ushiku; Tatsuya Harada (CoRR, 2018)

Generating Easy-to-Understand Referring Expressions for Target Identifications. - Mikihiro Tanaka; Takayuki Itamochi; Kenichi Narioka; Ikuro Sato; Yoshitaka Ushiku; Tatsuya Harada (ICCV, 2019)

Breaking Inter-Layer Co-Adaptation by Classifier Anonymization. - Ikuro Sato; Kohta Ishikawa; Guoqing Liu; Masayuki Tanaka 001 (ICML, 2019)

A New Way of Estimating Distances to Foregoing Vehicles from a Monocular Camera with Error Modeling. - Teppei Suzuki; Ikuro Sato (IV, 2019)

Adversarial Transformations for Semi-Supervised Learning. - Teppei Suzuki; Ikuro Sato (AAAI, 2020)

Disentangling Latent Groups Of Factors. - Nakamasa Inoue; Ryota Yamada; Rei Kawakami; Ikuro Sato (ICIP, 2021)

Does End-to-End Trained Deep Model Always Perform Better than Non-End-to-End Counterpart? - Ikuro Sato; Guoqing Liu; Kohta Ishikawa; Teppei Suzuki; Masayuki Tanaka 001 (Image Processing: Algorithms and Systems, 2021)

Multi-task Curriculum Learning based on Gradient Similarity. - Hiroaki Igarashi; Kenichi Yoneji; Kohta Ishikawa; Rei Kawakami; Teppei Suzuki; Shingo Yashima; Ikuro Sato (BMVC, 2022)

Implicit Neural Representations for Variable Length Human Motion Generation. - Pablo Cervantes; Yusuke Sekikawa; Ikuro Sato; Koichi Shinoda (ECCV (17), 2022)

PoF: Post-Training of Feature Extractor for Improving Generalization. - Ikuro Sato; Ryota Yamada; Masayuki Tanaka 001; Nakamasa Inoue; Rei Kawakami (ICML, 2022)

Feature Space Particle Inference for Neural Network Ensembles. - Shingo Yashima; Teppei Suzuki; Kohta Ishikawa; Ikuro Sato; Rei Kawakami (ICML, 2022)

Informative Sample-Aware Proxy for Deep Metric Learning. - Aoyu Li; Ikuro Sato; Kohta Ishikawa; Rei Kawakami; Rio Yokota (MMAsia, 2022)

Fixed-Weight Difference Target Propagation. - Tatsukichi Shibuya; Nakamasa Inoue; Rei Kawakami; Ikuro Sato (AAAI, 2023)

Learning with Partial Forgetting in Modern Hopfield Networks. - Toshihiro Ota; Ikuro Sato; Rei Kawakami; Masayuki Tanaka 001; Nakamasa Inoue (AISTATS, 2023)

Pixel-level Contrastive Learning of Driving Videos with Optical Flow. - Tomoya Takahashi; Shingo Yashima; Kohta Ishikawa; Ikuro Sato; Rio Yokota (CVPR Workshops, 2023)

Multi Event Localization by Audio-Visual Fusion with Omnidirectional Camera and Microphone Array. - Wenru Zheng; Ryota Yoshihashi; Rei Kawakami; Ikuro Sato; Asako Kanezaki (CVPR Workshops, 2023)

EvIs-Kitchen: Egocentric Human Activities Recognition with Video and Inertial Sensor Data. - Yuzhe Hao; Kuniaki Uto; Asako Kanezaki; Ikuro Sato; Rei Kawakami; Koichi Shinoda (MMM (1), 2023)

Empirical Study on Optimizer Selection for Out-of-Distribution Generalization. - Hiroki Naganuma; Kartik Ahuja; Shiro Takagi; Tetsuya Motokawa; Rio Yokota; Kohta Ishikawa; Ikuro Sato; Ioannis Mitliagkas (Trans. Mach. Learn. Res., 2023)

Efficient Target Propagation by Deriving Analytical Solution. - Yanhao Bao; Tatsukichi Shibuya; Ikuro Sato; Rei Kawakami; Nakamasa Inoue (AAAI, 2024)

Learning Non-uniform Step Sizes for Neural Network Quantization. - Shinya Gongyo; Jinrong Liang; Mitsuru Ambai; Rei Kawakami; Ikuro Sato (ACCV (8), 2024)

A Simple Finetuning Strategy Based on Bias-Variance Ratios of Layer-Wise Gradients. - Mao Tomita; Ikuro Sato; Rei Kawakami; Nakamasa Inoue; Satoshi Ikehata; Masayuki Tanaka 001 (ACCV (8), 2024)

Gumbel-NeRF: Representing Unseen Objects as Part-Compositional Neural Radiance Fields. - Yusuke Sekikawa; Chingwei Hsu; Satoshi Ikehata; Rei Kawakami; Ikuro Sato (ICIP, 2024)

Transferring Teacher's Invariance to Student Through Data Augmentation Optimization. - Tamotsu Kurioka; Teppei Suzuki; Rei Kawakami; Ikuro Sato (ICONIP (7), 2024)

Rectified Lagrangian for Out-of-Distribution Detection in Modern Hopfield Networks. - Ryo Moriai; Nakamasa Inoue; Masayuki Tanaka 001; Rei Kawakami; Satoshi Ikehata; Ikuro Sato (AAAI, 2025)

Binary Stochastic Flip Optimization for Training Binary Neural Networks. - Tatsukichi Shibuya; Nakamasa Inoue; Rei Kawakami; Ikuro Sato (ICASSP, 2025)

CST: Character State Transformer for Object-Conditioned Human Motion Prediction. - Kuan-Wei Tseng; Rei Kawakami; Satoshi Ikehata; Ikuro Sato (WACV (Workshops), 2025)

Integrating Generative and Contrastive Approaches for Human Action Recognition. - Pablo Cervantes; Yusuke Sekikawa; Ikuro Sato; Koichi Shinoda (IEEE Access, 2025)

Masked Gated Linear Unit. - Yukito Tajima; Nakamasa Inoue; Yusuke Sekikawa; Ikuro Sato; Rio Yokota (CoRR, 2025)

PINO: Person-Interaction Noise Optimization for Long-Duration and Customizable Motion Generation of Arbitrary-Sized Groups. - Sakuya Ota; Qing Yu; Kent Fujiwara; Satoshi Ikehata; Ikuro Sato (CoRR, 2025)