2 citations · 5 across the 5 of their papers we have counts for
7 papers
Diff-ES: Stage-wise Structural Diffusion Pruning via Evolutionary Search
Zongfang Liu, Shengkun Tang, Zongliang Wu +2
Diffusion models have achieved remarkable success in high-fidelity image generation but remain computationally demanding due to their multi-step denoising process and large model s…
Realism Control One-step Diffusion for Real-World Image Super-Resolution
Zongliang Wu, Siming Zheng, Peng-Tao Jiang +1
Pre-trained diffusion models have shown great potential in real-world image super-resolution (Real-ISR) tasks by enabling high-resolution reconstructions. While one-step diffusion…
Prior-guided Hierarchical Harmonization Network for Efficient Image Dehazing
Xiongfei Su, Siyuan Li, Yuning Cui +7
Image dehazing is a crucial task that involves the enhancement of degraded images to recover their sharpness and textures. While vision Transformers have exhibited impressive resul…
Detail Matters: Mamba-Inspired Joint Unfolding Network for Snapshot Spectral Compressive Imaging
Mengjie Qin, Yuchao Feng, Zongliang Wu +2
In the coded aperture snapshot spectral imaging system, Deep Unfolding Networks (DUNs) have made impressive progress in recovering 3D hyperspectral images (HSIs) from a single 2D m…
Latent Diffusion Prior Enhanced Deep Unfolding for Snapshot Spectral Compressive Imaging
Zongliang Wu, Ruiying Lu, Ying Fu +1
Snapshot compressive spectral imaging reconstruction aims to reconstruct three-dimensional spatial-spectral images from a single-shot two-dimensional compressed measurement. Existi…
Cooperative Hardware-Prompt Learning for Snapshot Compressive Imaging
Jiamian Wang, Zongliang Wu, Yulun Zhang +3
Existing reconstruction models in snapshot compressive imaging systems (SCI) are trained with a single well-calibrated hardware instance, making their performance vulnerable to har…