Face hallucination method and system of global-local separation attention mechanism

A local separation and super-resolution technology, applied in the field of computer vision face super-resolution, which can solve the problems that face super-resolution reconstruction algorithms cannot use both global and local attention mechanisms at the same time, and face image reconstruction performance limitations. , to achieve the effect of enhancing feature expression ability and improving reconstruction performance

Active Publication Date: 2020-12-11
WUHAN INSTITUTE OF TECHNOLOGY
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Problems solved by technology

[0006] In view of the above defects or improvement needs of the prior art, the present invention proposes a face super-resolution method and system based on a global-local separation attention mechanism, which solves the pro

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  • Face hallucination method and system of global-local separation attention mechanism
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[0037] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not constitute a conflict with each other.

[0038] The face super-resolution method based on the global-local separation attention mechanism of the embodiment of the present invention, such as figure 1 shown, including the following steps:

[0039] S1: Build a downsampling module to downsample the high-resolution face image to the target low-resolution face image;

[0040] In the embodiment of the present invention, a bicubic interpolat...

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Abstract

The invention discloses a face hallucination method and system based on a global-local separation attention mechanism. The method comprises the following steps: down-sampling a high-resolution face image to a target low-resolution face image; segmenting the target low-resolution image into blocks so as to extract a rough face feature map after mutually overlapped image blocks are obtained; constructing a separation attention network as a fine feature extractor, inputting the rough face features into the separation attention network to obtain a fine face feature map, wherein the separation attention network comprises a plurality of global-local separation attention groups, each global-local separation attention group generates two pieces of local attention and uses one global attention module to fuse different local attention, so that the local attention interacts across the feature groups, and the global attention of the network is realized; up-sampling the obtained face fine feature map; and reconstructing the up-sampled face feature map into a high-resolution face image of the target. According to the method, a face hallucination image with higher quality can be generated.

Description

technical field [0001] The invention belongs to the field of computer vision human face super-resolution, and more specifically relates to a method and system for human face super-resolution based on a global-local separation attention mechanism. Background technique [0002] Face super-resolution (face hallucination) is a special field of super-resolution (Super-Resolution, SR), which is a method to infer high-resolution images from input low-resolution (Low Resolution, LR) face images. (High Resolution, HR) image technology, which can significantly enhance the details of low-resolution face images. In real-world surveillance scenarios, the distance between the imaging sensor and the face is often too large, resulting in low-resolution face images. Using face super-resolution to restore high-resolution face images is helpful for target person identification. This method plays an important role in many applications such as face detection, face recognition and analysis. ...

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Application Information

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IPC IPC(8): G06T3/40G06K9/00
CPCG06T3/4053G06V40/168
Inventor 卢涛王元植张彦铎吴云韬
Owner WUHAN INSTITUTE OF TECHNOLOGY
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