Local descriptor generation method and device, electronic equipment and computer program product

A technology of local descriptors and descriptors, applied in the field of computer vision, can solve the problems of invariance and low robustness, and achieve the effects of improving robustness, improving accuracy, and enhancing invariance

Pending Publication Date: 2022-07-12
INST OF AUTOMATION CHINESE ACAD OF SCI +1
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0004] The present invention provides a local descriptor generation method, device, electronic equipment and computer program products, which are used to so

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  • Local descriptor generation method and device, electronic equipment and computer program product
  • Local descriptor generation method and device, electronic equipment and computer program product
  • Local descriptor generation method and device, electronic equipment and computer program product

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Embodiment Construction

[0051]In order to make the objectives, technical solutions and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention. , not all examples. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0052] Combine below Figure 1-Figure 8 The local descriptor generation method of the present invention is described.

[0053] figure 1 is one of the schematic flow charts of the local descriptor generation method provided by the present invention, such as figure 1 As shown, the method includes:

[0054] Step 110, generating a cross-domain data set, where the cross-domain data set includes multiple pairs of imag...

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Abstract

The invention provides a local descriptor generation method and device, electronic equipment and a computer program product, and the method comprises the steps: generating a cross-domain data set which comprises a plurality of image pairs; according to the scale feature map of the cross-domain data set, feature-level domain self-adaptive supervision information is obtained; pixel-level cross-domain consistency supervision information and descriptor loss information are obtained according to the dense descriptors of the feature-level domain self-adaptive supervision information; based on the combination of the feature-level domain adaptive supervision information, the pixel-level cross-domain consistency supervision information and the descriptor loss information, total loss is determined, the total loss is used for supervision training of the network, and a local descriptor is obtained. According to the method, the invariance and robustness of the local descriptor can be enhanced, and the precision of the descriptor on an image matching task is improved.

Description

technical field [0001] The present invention relates to the technical field of computer vision, and in particular, to a method, apparatus, electronic device and computer program product for generating a local descriptor. Background technique [0002] Currently, extracting accurate and efficient local feature descriptors is an essential processing step for various computer vision applications, such as mobile visual search, visual tracking, image matching, image retrieval, and visual localization. While in traditional handcrafted feature extraction methods, SIFT plays a crucial role in computer vision tasks with scale invariance and rotation invariance. Advances in deep learning have resulted in a large gap between the learned local descriptors and classical methods. In recent years, models that jointly learn keypoint detection and descriptors have achieved better performance in image matching and visual localization. Unlike patch-based feature descriptors, these methods ins...

Claims

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Application Information

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IPC IPC(8): G06V10/40G06V10/44G06K9/62G06N3/04G06N3/08G06T3/00G06V10/74G06V10/774G06V10/764G06V10/82
CPCG06T3/0012G06N3/08G06N3/045G06F18/22G06F18/214G06F18/241
Inventor 许镕涛王常维徐士彪孟维亮张晓鹏
Owner INST OF AUTOMATION CHINESE ACAD OF SCI
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