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To achieve disentangled image manipulation, previous works depend heavily on manual annotation. Meanwhile, the available manipulations are limited to a pre-defined set the models were trained for. We propose a novel framework, i.e., Predict, Prevent, and Evaluate (PPE), for disentangled text-driven image manipulation that requires little manual annotation while being applicable to a wide variety of manipulations. Our method approaches the targets by deeply exploiting the power of thearXiv:2111.13333v2 fatcat:ewsrexmxmbbrthvhrftgm73k2i