Revisiting single image depth estimation: Toward higher resolution maps with accurate object boundaries J Hu, M Ozay, Y Zhang, T Okatani IEEE Winter Conference on Applications of Computer Vision (WACV), 1043-1051, 2019 | 455 | 2019 |
Improved fusion of visual and language representations by dense symmetric co-attention for visual question answering DK Nguyen, T Okatani IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 6087-6096, 2018 | 345 | 2018 |
Dual residual networks leveraging the potential of paired operations for image restoration X Liu, M Suganuma, Z Sun, T Okatani IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 7007-7016, 2019 | 244 | 2019 |
Shape reconstruction from an endoscope image by shape from shading technique for a point light source at the projection center T Okatani, K Deguchi Computer vision and image understanding 66 (2), 119-131, 1997 | 231 | 1997 |
A vision-based method for crack detection in gusset plate welded joints of steel bridges using deep convolutional neural networks CV Dung, H Sekiya, S Hirano, T Okatani, C Miki Automation in Construction 102, 217-229, 2019 | 212 | 2019 |
On the Wiberg algorithm for matrix factorization in the presence of missing components T Okatani, K Deguchi International Journal of Computer Vision 72, 329-337, 2007 | 179 | 2007 |
Change detection from a street image pair using cnn features and superpixel segmentation K Sakurada, T Okatani British Machine Vision Conference (BMVC) 61, 1-12, 2015 | 175* | 2015 |
Separation of reflection components by sparse non-negative matrix factorization Y Akashi, T Okatani Asian Conference on Computer Vision (ACCV), 611-625, 2015 | 124 | 2015 |
Object tracking by the mean-shift of regional color distribution combined with the particle-filter algorithms K Deguchi, O Kawanaka, T Okatani Proceedings of the 17th International Conference on Pattern Recognition …, 2004 | 119 | 2004 |
Exploiting the potential of standard convolutional autoencoders for image restoration by evolutionary search M Suganuma, M Ozay, T Okatani International Conference on Machine Learning, 4771-4780, 2018 | 108 | 2018 |
Attention-based adaptive selection of operations for image restoration in the presence of unknown combined distortions M Suganuma, X Liu, T Okatani IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 9039-9048, 2019 | 106 | 2019 |
Efficient algorithm for low-rank matrix factorization with missing components and performance comparison of latest algorithms T Okatani, T Yoshida, K Deguchi International Conference on Computer Vision (ICCV), 842-849, 2011 | 105 | 2011 |
Hyperparameter-free out-of-distribution detection using cosine similarity E Techapanurak, M Suganuma, T Okatani Proceedings of the Asian conference on computer vision, 2020 | 103* | 2020 |
Grit: Faster and better image captioning transformer using dual visual features VQ Nguyen, M Suganuma, T Okatani European Conference on Computer Vision, 167-184, 2022 | 100 | 2022 |
Detecting changes in 3D structure of a scene from multi-view images captured by a vehicle-mounted camera K Sakurada, T Okatani, K Deguchi IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 137-144, 2013 | 97 | 2013 |
Visualization of convolutional neural networks for monocular depth estimation J Hu, Y Zhang, T Okatani IEEE/CVF International Conference on Computer Vision (ICCV), 3869-3878, 2019 | 93 | 2019 |
Deep learning T Okatani Machine Learning Professional Series, Kodansha Ltd, 2015 | 91 | 2015 |
Mix and Match: Joint Model for Clothing and Attribute Recognition. K Yamaguchi, T Okatani, K Sudo, K Murasaki, Y Taniguchi British Machine Vision Conference (BMVC) 1 (2), 4, 2015 | 88 | 2015 |
Autocalibration of a projector-camera system T Okatani, K Deguchi IEEE Transactions on Pattern Analysis and Machine Intelligence 27 (12), 1845 …, 2005 | 83 | 2005 |
Automatic attribute discovery with neural activations S Vittayakorn, T Umeda, K Murasaki, K Sudo, T Okatani, K Yamaguchi European Conference on Computer Vision (ECCV), 252-268, 2016 | 72 | 2016 |