Multiple-Hypothesis Affine Region Estimation with Anisotropic LoG Filters. - Takahiro Hasegawa; Mitsuru Ambai; Kohta Ishikawa; Gou Koutaki; Yuji Yamauchi; Takayoshi Yamashita; Hironobu Fujiyoshi (ICCV, 2015)

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

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

Constant Velocity 3D Convolution. - Yusuke Sekikawa; Kohta Ishikawa; Hideo Saito (IEEE Access, 2018)

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

CorsNet: 3D Point Cloud Registration by Deep Neural Network. - Akiyoshi Kurobe; Yusuke Sekikawa; Kohta Ishikawa; Hideo Saito (IEEE Robotics Autom. Lett., 2020)

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)

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)

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