Blind Face Restoration
Blind face restoration (BFR) aims to recover high-quality images of faces from degraded inputs with unknown corruption types. Current research heavily utilizes diffusion models, often incorporating 3D facial priors or learned codebooks to guide the restoration process and improve realism while preserving identity. These advancements are driven by the need for robust and efficient methods applicable to real-world scenarios, including video and under-display camera images, and are evaluated on increasingly diverse and challenging benchmark datasets. The resulting improvements in BFR have significant implications for applications such as face recognition, video conferencing, and image forensics.
Papers
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