Fine-tuning visual models has been widely shown promising performance on many
downstream visual tasks. With the surprising development of pre-trained visual foundation …

By integrating certain optimization solvers with deep neural networks, deep unfolding
network (DUN) with good interpretability and high performance has attracted growing …

Map** a truncated optimization method into a deep neural network, deep unfolding
network (DUN) has attracted growing attention in compressive sensing (CS) due to its good …

Deep unfolding network (DUN) that unfolds the optimization algorithm into a deep neural
network has achieved great success in compressive sensing (CS) due to its good …

Map** a truncated optimization method into a deep neural network, deep proximal
unrolling network has attracted attention in compressive sensing due to its good …

By absorbing the merits of both the model-and data-driven methods, deep physics-engaged
learning scheme achieves high-accuracy and interpretable image reconstruction. It has …

As a kind of network structure increasingly studied in compressive sensing (CS), deep
unfolding networks (DUNs), which unroll the iterative reconstruction procedure as deep …

Mask based lensless imagers have huge application prospects due to their ultra-thin body.
However, the visual perception of the restored images is poor due to the ill conditioned …

Deep Unfolding Networks (DUNs) have demonstrated remarkable success in compressed
sensing by integrating optimization solvers with deep neural networks. The issue of …

Image restoration schemes based on the pre-trained deep models have received great
attention due to their unique flexibility for solving various inverse problems. In particular, the …