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Pre-Trained Low-Rank Tensor Decomposition for Multi-Dimensional Image Recovery

arXiv · AI, language, vision and robotics · article · Sep 11, 2026 · UTC

Recently, tensor decompositions are prevalent for multi-dimensional image representation, which learn the instance-specific structure of each image from scratch. However, tensor decompositions neglect the common structure across different images, leading to limited semantic modeling capability, high computational cost, and a large number of learnable parameters. To address this challenge, we suggest the first pre-trained low-rank tensor decomposition (PLTD) framework, which organically integrates the pre-trained large vision model into the classical tensor decomposition framework. Beyond the s

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