“Blind” visual inference by composition

Pattern Recognition Letters(2019)

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摘要
“Blind” visual inference can often be performed by exploiting the internal redundancy inside a single visual datum (whether an image or a video). The strong recurrence of patches inside a single image/video provides a powerful data-specific priorfor solving complex visual tasks in a “blind” manner. The term “blind” is used here with a double meaning: (i) Blind in the sense that we can make sophisticated inferences about things we have never seen before, in a totally unsupervised way, with no prior examples or training; and (ii) Blind in the sense that we can solve complex Inverse-Problems, even when the forward degradation model is unknown. This paper briefly reviews this approach and its applicability to a variety of vision problems, ranging from low-level to high-level, including:
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