Robust tensor completion using general unitary transforms in tensor SVD yields lower tubal rank and improved PSNR recovery on image and video datasets compared to Fourier-based approaches.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
verdicts
UNVERDICTED 2representative citing papers
A new TWCTV regularizer using weighted Schatten-p norms on gradients and adaptive sparse weighting in the M-product framework is proposed for robust tensor completion, with an ADMM solver and claimed superior performance on image tasks.
citing papers explorer
-
Robust Tensor Completion Using Transformed Tensor SVD
Robust tensor completion using general unitary transforms in tensor SVD yields lower tubal rank and improved PSNR recovery on image and video datasets compared to Fourier-based approaches.
-
Robust Low-Rank Tensor Completion based on M-product with Weighted Correlated Total Variation and Sparse Regularization
A new TWCTV regularizer using weighted Schatten-p norms on gradients and adaptive sparse weighting in the M-product framework is proposed for robust tensor completion, with an ADMM solver and claimed superior performance on image tasks.