SeBIR: Semantic-guided burst image restoration.

Burst image restoration methods offer the possibility of recovering faithful scene details from multiple low-quality snapshots captured by hand-held devices in adverse scenarios, thereby attracting increasing attention in recent years. However, individual frames in a burst typically suffer from inter-frame misalignments, leading to ghosting artifacts. Besides, existing methods indiscriminately handle all burst frames, struggling to seamlessly remove the corrupted information due to the neglect of multi-frame spatio-temporal varying degradation.