6 papers
Detailed Geometry and Appearance from Opportunistic Motion
Ryosuke Hirai, Kohei Yamashita, Antoine Guédon +3
Reconstructing 3D geometry and appearance from a sparse set of fixed cameras is a foundational task with broad applications, yet it remains fundamentally constrained by the limited…
M-PhyGs: Multi-Material Object Dynamics from Video
Norika Wada, Kohei Yamashita, Ryo Kawahara +1
Knowledge of the physical material properties governing the dynamics of a real-world object becomes necessary to accurately anticipate its response to unseen interactions. Existing…
MAtCha Gaussians: Atlas of Charts for High-Quality Geometry and Photorealism From Sparse Views
Antoine Guédon, Tomoki Ichikawa, Kohei Yamashita +1
We present a novel appearance model that simultaneously realizes explicit high-quality 3D surface mesh recovery and photorealistic novel view synthesis from sparse view samples. Ou…
Correspondences of the Third Kind: Camera Pose Estimation from Object Reflection
Kohei Yamashita, Vincent Lepetit, Ko Nishino
Computer vision has long relied on two kinds of correspondences: pixel correspondences in images and 3D correspondences on object surfaces. Is there another kind, and if there is,…
DeepShaRM: Multi-View Shape and Reflectance Map Recovery Under Unknown Lighting
Kohei Yamashita, Shohei Nobuhara, Ko Nishino
Geometry reconstruction of textureless, non-Lambertian objects under unknown natural illumination (i.e., in the wild) remains challenging as correspondences cannot be established a…
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…