42 citations · 61 across the 7 of their papers we have counts for
8 papers
Restoring without Forgetting: Filter-Level Continual Image Restoration via Parameter-Space Integrated Gradients
Xin Feng, Jin Zhao, Yizhen Zhang +3
Adapting image restoration models to a stream of new tasks without revisiting past data remains challenging due to catastrophic forgetting. In this work, we propose Restoring witho…
Hierarchical Contrastive Learning for Pattern-Generalizable Image Corruption Detection
Xin Feng, Yifeng Xu, Guangming Lu +1
Effective image restoration with large-size corruptions, such as blind image inpainting, entails precise detection of corruption region masks which remains extremely challenging du…
Learning Generalizable Latent Representations for Novel Degradations in Super Resolution
Fengjun Li, Xin Feng, Fanglin Chen +2
Typical methods for blind image super-resolution (SR) focus on dealing with unknown degradations by directly estimating them or learning the degradation representations in a latent…
Learning Sequence Representations by Non-local Recurrent Neural Memory
Wenjie Pei, Xin Feng, Canmiao Fu +3
The key challenge of sequence representation learning is to capture the long-range temporal dependencies. Typical methods for supervised sequence representation learning are built…
Global-Local Stepwise Generative Network for Ultra High-Resolution Image Restoration
Xin Feng, Haobo Ji, Wenjie Pei +2
While the research on image background restoration from regular size of degraded images has achieved remarkable progress, restoring ultra high-resolution (e.g., 4K) images remains…
U2-Former: A Nested U-shaped Transformer for Image Restoration
Haobo Ji, Xin Feng, Wenjie Pei +2
While Transformer has achieved remarkable performance in various high-level vision tasks, it is still challenging to exploit the full potential of Transformer in image restoration.…
Generative Memory-Guided Semantic Reasoning Model for Image Inpainting
Xin Feng, Wenjie Pei, Fengjun Li +3
Most existing methods for image inpainting focus on learning the intra-image priors from the known regions of the current input image to infer the content of the corrupted regions…
Deep-Masking Generative Network: A Unified Framework for Background Restoration from Superimposed Images
Xin Feng, Wenjie Pei, Zihui Jia +3
Restoring the clean background from the superimposed images containing a noisy layer is the common crux of a classical category of tasks on image restoration such as image reflecti…