Deep Cascaded Bi-Network for Face Hallucination

Understand

We present a novel framework for hallucinating faces of unconstrained poses and with very low resolution (face size as small as 5pxIOD).

• In contrast to existing studies that mostly ignore or assume pre-aligned face spatial configuration (e.g.
• facial landmarks localization or dense correspondence field), we alternatingly optimize two complementary tasks, namely face hallucination and dense correspondence field estimation, in a unified framework.
• In addition, we propose a new gated deep bi-network that contains two functionality-specialized branches to recover different levels of texture details.