eess.IV · 2026-09-16 · No. 115
Image and Video Processing, 2026-09-16.
1 new papers in eess.IV. Titles, authors,
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01 — The papers
1 entries-
01
Quantum-Inspired Trainable and Parameter-Efficient Tensor Networks for Image Inpainting
Shiwen An, Konstantinos Slavakis
eess.IV · cs.CV · cs.LG
This work introduces quantum-inspired tensor-network circuits as trainable transforms for image inpainting. Among the proposed architectures, the diagonal quantum Fourier transform (QFT) relaxation is invertible with $O(N^2 \log N)$ computational cost for $N\times N$ images, inherently preserving minimum coherence throughout training via its circuit structure and eliminating the need for explicit coherence penalties. Unconstrained...
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