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Found 8 papers, 1 papers with code
Improving Spherical Image Resampling through Viewport-Adaptivity
The conversion between different spherical image and video projection formats requires highly accurate resampling techniques in order to minimize the inevitable loss of information.
Joint Geometry and Attribute Upsampling of Point Clouds Using Frequency-Selective Models with Overlapped Support
The attribute model is evaluated for the upsampled geometry positions.
Jointly Resampling and Reconstructing Corrupted Images for Image Classification using Frequency-Selective Mesh-to-Grid Resampling
Mostly, the visual data is transmitted from the application side to a central server where the interpretation is conducted.
Frame Rate Up-Conversion Using Key Point Agnostic Frequency-Selective Mesh-to-Grid Resampling
High frame rates are desired in many fields of application.
Increasing the Accuracy of a Neural Network Using Frequency Selective Mesh-to-Grid Resampling
Using an extensive experimental evaluation we show that depending on the network architecture and classification task the application of FSMR during training aids the learning process.
Frequency-Selective Geometry Upsampling of Point Clouds
The demand for high-resolution point clouds has increased throughout the last years.
Frequency-Selective Mesh-to-Mesh Resampling for Color Upsampling of Point Clouds
Secondly, we propose to apply a novel Frequency-Selective Mesh-to-Mesh Resampling (FSMMR) technique for the interpolation of the points in 2D.
Key Point Agnostic Frequency-Selective Mesh-to-Grid Image Resampling using Spectral Weighting
A state-of-the-art high quality model-based resampling technique is frequency-selective mesh-to-grid resampling which requires pre-estimation of key points.
