Sharing the Learned Knowledge-base to Estimate Convolutional Filter Parameters for Continual Image Restoration

ArXi:2511.05421v2 Announce Type: replace Continual learning is an emerging topic in the field of deep learning, where a model is expected to learn continuously for new upcoming tasks without forgetting previous experiences. This field has witnessed numerous advancements, but few works have been attempted in the direction of image restoration. Handling large image sizes and the divergent nature of various degradation poses a unique challenge in the restoration domain.