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Found 6 papers, 2 papers with code
Deep Depth from Focal Stack with Defocus Model for Camera-Setting Invariance
Our method takes a plane sweep volume as input for the constraint between scene depth, defocus images, and camera settings, and this intermediate representation enables depth estimation with different camera settings at training and test times.
Dehazing Cost Volume for Deep Multi-view Stereo in Scattering Media with Airlight and Scattering Coefficient Estimation
We also propose a method of estimating scattering parameters, such as airlight, and a scattering coefficient, which are required for our dehazing cost volume.
Partially-Shared Variational Auto-encoders for Unsupervised Domain Adaptation with Target Shift
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.
Defogging Kinect: Simultaneous Estimation of Object Region and Depth in Foggy Scenes
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.
Photometric Stereo in Participating Media Considering Shape-Dependent Forward Scatter
Images captured in participating media such as murky water, fog, or smoke are degraded by scattered light.
Outlier Cluster Formation in Spectral Clustering
The highlights of this paper are the following two mathematical observations: first, spectral clustering's intrinsic property of an outlier cluster formation, and second, the singularity of an outlier cluster with a valid cluster number.
