Daiki Ikami

Publication Activity (10 Years)

Years Active: 2017-2023
Publications (10 Years): 24

Top Topics

Depth Estimation

Efficient Algorithms For Solving

Nonlinear Least Squares

Supervised Learning

Top Venues

Publications

Atsuyuki Miyai, Qing Yu, Daiki Ikami, Go Irie, Kiyoharu Aizawa
Rethinking Rotation in Self-Supervised Contrastive Learning: Adaptive Positive or Negative Data Augmentation. WACV (2023)
Atsuyuki Miyai, Qing Yu, Daiki Ikami, Go Irie, Kiyoharu Aizawa
Rethinking Rotation in Self-Supervised Contrastive Learning: Adaptive Positive or Negative Data Augmentation. CoRR (2022)
Qing Yu, Daiki Ikami, Go Irie, Kiyoharu Aizawa
Self-Labeling Framework for Novel Category Discovery over Domains. AAAI (2022)
Daiki Tanaka, Daiki Ikami, Kiyoharu Aizawa
A Novel Perspective for Positive-Unlabeled Learning via Noisy Labels. CoRR (2021)
Yu Mitsuzumi, Go Irie, Daiki Ikami, Takashi Shibata
Generalized Domain Adaptation. CVPR (2021)
Takashi Shibata, Go Irie, Daiki Ikami, Yu Mitsuzumi
Learning with Selective Forgetting. IJCAI (2021)
Yu Mitsuzumi, Go Irie, Daiki Ikami, Takashi Shibata
Generalized Domain Adaptation. CoRR (2021)
Daiki Ikami, Go Irie, Takashi Shibata
Constrained Weight Optimization for Learning without Activation Normalization. WACV (2021)
Go Irie, Daiki Ikami, Takahito Kawanishi, Kunio Kashino
Cascaded Transposed Long-Range Convolutions for Monocular Depth Estimation. ACCV (3) (2020)
Takumi Kawashima, Qing Yu, Akari Asai, Daiki Ikami, Kiyoharu Aizawa
The Aleatoric Uncertainty Estimation Using a Separate Formulation with Virtual Residuals. CoRR (2020)
Qing Yu, Daiki Ikami, Go Irie, Kiyoharu Aizawa
Multi-Task Curriculum Framework for Open-Set Semi-Supervised Learning. CoRR (2020)
Shota Horiguchi, Daiki Ikami, Kiyoharu Aizawa
Significance of Softmax-Based Features in Comparison to Distance Metric Learning-Based Features. IEEE Trans. Pattern Anal. Mach. Intell. 42 (5) (2020)
Takumi Kawashima, Qing Yu, Akari Asai, Daiki Ikami, Kiyoharu Aizawa
The Aleatoric Uncertainty Estimation Using a Separate Formulation with Virtual Residuals. ICPR (2020)
Qing Yu, Daiki Ikami, Go Irie, Kiyoharu Aizawa
Multi-task Curriculum Framework for Open-Set Semi-supervised Learning. ECCV (12) (2020)
Akari Asai, Daiki Ikami, Kiyoharu Aizawa
Multi-Task Learning based on Separable Formulation of Depth Estimation and its Uncertainty. CVPR Workshops (2019)
Koki Tsubota, Daiki Ikami, Kiyoharu Aizawa
Synthesis of Screentone Patterns of Manga Characters. ISM (2019)
Daiki Tanaka, Daiki Ikami, Toshihiko Yamasaki, Kiyoharu Aizawa
Joint Optimization Framework for Learning With Noisy Labels. CVPR (2018)
Daiki Ikami, Toshihiko Yamasaki, Kiyoharu Aizawa
Fast and Robust Estimation for Unit-Norm Constrained Linear Fitting Problems. CVPR (2018)
Daiki Tanaka, Daiki Ikami, Toshihiko Yamasaki, Kiyoharu Aizawa
Joint Optimization Framework for Learning with Noisy Labels. CoRR (2018)
Akito Takeki, Daiki Ikami, Go Irie, Kiyoharu Aizawa
Parallel Grid Pooling for Data Augmentation. CoRR (2018)
Daiki Ikami, Toshihiko Yamasaki, Kiyoharu Aizawa
Local and Global Optimization Techniques in Graph-Based Clustering. CVPR (2018)
Daiki Ikami, Toshihiko Yamasaki, Kiyoharu Aizawa
Residual Expansion Algorithm: Fast and Effective Optimization for Nonconvex Least Squares Problems. CoRR (2017)
Daiki Ikami, Toshihiko Yamasaki, Kiyoharu Aizawa
Residual Expansion Algorithm: Fast and Effective Optimization for Nonconvex Least Squares Problems. CVPR (2017)
Shota Horiguchi, Daiki Ikami, Kiyoharu Aizawa
Significance of Softmax-based Features in Comparison to Distance Metric Learning-based Features. CoRR (2017)