121 citations · 136 across the 6 of their papers we have counts for
8 papers
Multi-View Neural Surface Reconstruction with Structured Light
Chunyu Li, Taisuke Hashimoto, Eiichi Matsumoto +1
Three-dimensional (3D) object reconstruction based on differentiable rendering (DR) is an active research topic in computer vision. DR-based methods minimize the difference between…
Monocular Differentiable Rendering for Self-Supervised 3D Object Detection
Deniz Beker, Hiroharu Kato, Mihai Adrian Morariu +4
3D object detection from monocular images is an ill-posed problem due to the projective entanglement of depth and scale. To overcome this ambiguity, we present a novel self-supervi…
Differentiable Rendering: A Survey
Hiroharu Kato, Deniz Beker, Mihai Morariu +4
Deep neural networks (DNNs) have shown remarkable performance improvements on vision-related tasks such as object detection or image segmentation. Despite their success, they gener…
Self-supervised Learning of 3D Objects from Natural Images
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. Since this is a s…
Learning View Priors for Single-view 3D Reconstruction
Hiroharu Kato, Tatsuya Harada
There is some ambiguity in the 3D shape of an object when the number of observed views is small. Because of this ambiguity, although a 3D object reconstructor can be trained using…
Neural 3D Mesh Renderer
Hiroharu Kato, Yoshitaka Ushiku, Tatsuya Harada
For modeling the 3D world behind 2D images, which 3D representation is most appropriate? A polygon mesh is a promising candidate for its compactness and geometric properties. Howev…