7 papers
SegDem: Segmentation helps Demosaicing
Ping Chen, Xiangming Wang, Yongyong Chen +5
Image demosaicing reconstructs a full-color image from incomplete color measurements produced by a sensor covered with a color filter array (CFA). Most existing methods formulate d…
Agentic Flow Steering and Parallel Rollout Search for Spatially Grounded Text-to-Image Generation
Ping Chen, Daoxuan Zhang, Xiangming Wang +3
Precise Text-to-Image (T2I) generation has achieved great success but is hindered by the limited relational reasoning of static text encoders and the error accumulation in open-loo…
Deep LoRA-Unfolding Networks for Image Restoration
Xiangming Wang, Haijin Zeng, Benteng Sun +4
Deep unfolding networks (DUNs), combining conventional iterative optimization algorithms and deep neural networks into a multi-stage framework, have achieved remarkable accomplishm…
HSI-VAR: Rethinking Hyperspectral Restoration through Spatial-Spectral Visual Autoregression
Xiangming Wang, Benteng Sun, Yungeng Liu +4
Hyperspectral images (HSIs) capture richer spatial-spectral information beyond RGB, yet real-world HSIs often suffer from a composite mix of degradations, such as noise, blur, and…
Vision-Language Controlled Deep Unfolding for Joint Medical Image Restoration and Segmentation
Ping Chen, Zicheng Huang, Xiangming Wang +4
We propose VL-DUN, a principled framework for joint All-in-One Medical Image Restoration and Segmentation (AiOMIRS) that bridges the gap between low-level signal recovery and high-…
Vision-Language Gradient Descent-driven All-in-One Deep Unfolding Networks
Haijin Zeng, Xiangming Wang, Yongyong Chen +2
Dynamic image degradations, including noise, blur and lighting inconsistencies, pose significant challenges in image restoration, often due to sensor limitations or adverse environ…