Search Results for author: Motoharu Sonogashira

Found 4 papers, 2 papers with code

ManifoldNeRF: View-dependent Image Feature Supervision for Few-shot Neural Radiance Fields

no code implementations20 Oct 2023 Daiju Kanaoka, Motoharu Sonogashira, Hakaru Tamukoh, Yasutomo Kawanishi

DietNeRF is an extension of NeRF that aims to achieve this task from only a few images by introducing a new loss function for unknown viewpoints with no input images.

Novel View Synthesis

Dehazing Cost Volume for Deep Multi-view Stereo in Scattering Media with Airlight and Scattering Coefficient Estimation

1 code implementation18 Nov 2020 Yuki Fujimura, Motoharu Sonogashira, Masaaki Iiyama

We also propose a method of estimating scattering parameters, such as airlight, and a scattering coefficient, which are required for our dehazing cost volume.

3D Reconstruction Depth Estimation +1

Partially-Shared Variational Auto-encoders for Unsupervised Domain Adaptation with Target Shift

1 code implementation ECCV 2020 Ryuhei Takahashi, Atsushi Hashimoto, Motoharu Sonogashira, Masaaki Iiyama

In practice, this is an important problem in UDA; as we do not know labels in target domain datasets, we do not know whether or not its distribution is identical to that in the source domain dataset.

General Classification Pose Estimation +2

Defogging Kinect: Simultaneous Estimation of Object Region and Depth in Foggy Scenes

no code implementations1 Apr 2019 Yuki Fujimura, Motoharu Sonogashira, Masaaki Iiyama

The scattering component is saturated, so it does not depend on the scene depth, and received signals bouncing off distant points are negligible due to light attenuation in the participating media, so the observation of such a point contains only a scattering component.

3D Reconstruction Depth Estimation +1

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