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Found 4 papers, 0 papers with code
Correspondences of the Third Kind: Camera Pose Estimation from Object Reflection
In this paper, we introduce correspondences of the third kind we call reflection correspondences and show that they can help estimate camera pose by just looking at objects without relying on the background.
DeepShaRM: Multi-View Shape and Reflectance Map Recovery Under Unknown Lighting
We introduce a novel deep reflectance map estimation network that recovers the camera-view reflectance maps from the surface normals of the current geometry estimate and the input multi-view images.
nLMVS-Net: Deep Non-Lambertian Multi-View Stereo
Our key idea is to formulate MVS as an end-to-end learnable network, which we refer to as nLMVS-Net, that seamlessly integrates radiometric cues to leverage surface normals as view-independent surface features for learned cost volume construction and filtering.
3D-GMNet: Single-View 3D Shape Recovery as A Gaussian Mixture
In this paper, we introduce 3D-GMNet, a deep neural network for 3D object shape reconstruction from a single image.
