no code implementations • 22 Nov 2022 • Chunyu Li, Taisuke Hashimoto, Eiichi Matsumoto, Hiroharu Kato
Three-dimensional (3D) object reconstruction based on differentiable rendering (DR) is an active research topic in computer vision.
no code implementations • ECCV 2020 • Deniz Beker, Hiroharu Kato, Mihai Adrian Morariu, Takahiro Ando, Toru Matsuoka, Wadim Kehl, Adrien Gaidon
3D object detection from monocular images is an ill-posed problem due to the projective entanglement of depth and scale.
3D Object Detection 3D Object Detection From Monocular Images +4
no code implementations • 22 Jun 2020 • Hiroharu Kato, Deniz Beker, Mihai Morariu, Takahiro Ando, Toru Matsuoka, Wadim Kehl, Adrien Gaidon
Deep neural networks (DNNs) have shown remarkable performance improvements on vision-related tasks such as object detection or image segmentation.
no code implementations • 20 Nov 2019 • Hiroharu Kato, Tatsuya Harada
We present a method to learn single-view reconstruction of the 3D shape, pose, and texture of objects from categorized natural images in a self-supervised manner.
no code implementations • CVPR 2019 • Hiroharu Kato, Tatsuya Harada
The discriminator is trained to distinguish the reconstructed views of the observed viewpoints from those of the unobserved viewpoints.
3 code implementations • CVPR 2018 • Hiroharu Kato, Yoshitaka Ushiku, Tatsuya Harada
Using this renderer, we perform single-image 3D mesh reconstruction with silhouette image supervision and our system outperforms the existing voxel-based approach.
Ranked #6 on 3D Object Reconstruction on Data3D−R2N2 (Avg F1 metric)
1 code implementation • 31 Oct 2017 • Andrew Shin, Leopold Crestel, Hiroharu Kato, Kuniaki Saito, Katsunori Ohnishi, Masataka Yamaguchi, Masahiro Nakawaki, Yoshitaka Ushiku, Tatsuya Harada
Automatic melody generation for pop music has been a long-time aspiration for both AI researchers and musicians.
Sound Multimedia Audio and Speech Processing
no code implementations • 9 Nov 2015 • Hiroharu Kato, Tatsuya Harada
Additionally, a method to measure naturalness can be complementary to Convolutional Neural Network (CNN) based features, which are known to be insensitive to the naturalness of images.
no code implementations • CVPR 2014 • Hiroharu Kato, Tatsuya Harada
The objective of this work is to reconstruct an original image from Bag-of-Visual-Words (BoVW).