Efficient Deep Unfolding Network with Hybrid-Attention Transformer for Large-Scale Single-Pixel Imaging
A deep unfolding network with hybrid-attention Transformer, dubbed HATNet, is proposed to efficiently reconstruct high-fidelity images from single-pixel measurements by exploiting the Kronecker structure of the single-pixel imaging model.