Research map / Learning theory and algorithms / Matrix and tensor methods
Low-Rank Tensor Completion with Total Variation for Visual Data Inpainting
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| add anisotropic TV regularization to unfolding-based LRTC (LRTC-TV-I vs HaLRTC) | HaLRTC · color image inpainting | RSE/PSNR | Helped |
| add TV regularization to Tucker-decomposition LRTC (LRTC-TV-II) | decomposition-based LRTC · color image inpainting | RSE/PSNR | Helped |
| use decomposition (nonconvex) formulation instead of unfolding (convex) | LRTC-TV · color image inpainting | RSE/PSNR | Helped |
| LRTC-TV-I vs FBCP as missing rate increases | LRTC-TV-I · color image inpainting | RSE/PSNR | Mixed |
| add TV regularization to LRTC | LRTC · BRAINIX MRI recovery | RSE/PSNR | Helped |
Closest papers by meaning
- Low-Rank Tensor Completion With a New Tensor Nuclear Norm Induced by Invertible Linear Transforms (CVPR 2019 · similarity 0.89)
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- Deep Rank-One Tensor Functional Factorization for Multi-Dimensional Data Recovery (AAAI 2025 · similarity 0.87)
- Low-Rank Tensor Transitions (LoRT) for Transferable Tensor Regression (ICML 2025 · similarity 0.87)
- Performance Gaps in Multi-view Clustering under the Nested Matrix-Tensor Model (ICLR 2024 · similarity 0.86)
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