Abstract: Highlights•Explore the idea of disentangled learning to solve ambiguous inverse problems with a more feasible bijective mapping.•Construct a hierarchical disentangled architecture, and achieve a better trade-off between performance and computational costs.•Powerful ability to solve diverse image restoration.
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