activity
20152022
most citedRecognizing Material Properties from Images

6 citations · 12 across the 7 of their papers we have counts for

collaborators

9 papers

cs.CV20201 cited

Differential Viewpoints for Ground Terrain Material Recognition

Jia Xue, Hang Zhang, Ko Nishino +1

Computational surface modeling that underlies material recognition has transitioned from reflectance modeling using in-lab controlled radiometric measurements to image-based repres…

cs.CV2020

Video Region Annotation with Sparse Bounding Boxes

Yuzheng Xu, Yang Wu, Nur Sabrina binti Zuraimi +2

Video analysis has been moving towards more detailed interpretation (e.g. segmentation) with encouraging progresses. These tasks, however, increasingly rely on densely annotated tr…

cs.CV20201 cited

Invertible Neural BRDF for Object Inverse Rendering

Zhe Chen, Shohei Nobuhara, Ko Nishino

We introduce a novel neural network-based BRDF model and a Bayesian framework for object inverse rendering, i.e., joint estimation of reflectance and natural illumination from a si…

cs.CV2019

3D-GMNet: Single-View 3D Shape Recovery as A Gaussian Mixture

Kohei Yamashita, Shohei Nobuhara, Ko Nishino

In this paper, we introduce 3D-GMNet, a deep neural network for 3D object shape reconstruction from a single image. As the name suggests, 3D-GMNet recovers 3D shape as a Gaussian m…

cs.CV2019

Appearance and Shape from Water Reflection

Ryo Kawahara, Meng-Yu Jennifer Kuo, Shohei Nobuhara +1

This paper introduces single-image geometric and appearance reconstruction from water reflection photography, i.e., images capturing direct and water-reflected real-world scenes. W…

cs.CV20186 cited

Recognizing Material Properties from Images

Gabriel Schwartz, Ko Nishino

Humans rely on properties of the materials that make up objects to guide our interactions with them. Grasping smooth materials, for example, requires care, and softness is an ideal…