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A text-based pedestrian retrieval self-supervised visual representation learning system and method

A technique for visual representation and learning methods, applied in the field of vision

Active Publication Date: 2022-08-05
GUIZHOU UNIV +1
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Problems solved by technology

[0004] Aiming at the above-mentioned deficiencies in the prior art, the present invention provides a text-based pedestrian retrieval self-supervised visual representation learning system and method, which solves the above-mentioned text-based pedestrian retrieval problem

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  • A text-based pedestrian retrieval self-supervised visual representation learning system and method
  • A text-based pedestrian retrieval self-supervised visual representation learning system and method
  • A text-based pedestrian retrieval self-supervised visual representation learning system and method

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Embodiment 1

[0068] like figure 1 As shown, a text-based pedestrian retrieval self-supervised visual representation learning system includes a text-image feature representation module, an object feature relationship module, an objective function module, an auxiliary module and a visual representation learning module connected in sequence; text-image feature representation module, used to extract text features and initial image features; object feature relationship module, used to build an object relationship inference model based on the initial image features, and output the final image features based on the object relationship inference model; objective function module, used to respectively The relational reasoning model, the final image feature and the text feature are calculated to obtain the ternary loss function, the image classification loss function and the text classification loss function; the auxiliary module is used to construct the pedestrian gender label by using the text featu...

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Abstract

The invention provides a text-based pedestrian retrieval self-supervised visual representation learning system and method. The visual features of the target person can be retrieved more accurately. Secondly, in order to use the object information in the picture, the present invention builds a model to extract the relationship between pedestrians and objects, and filters and summarizes these relationships. Through the above design, the present invention solves the problem that the existing network only pays attention to the similarity between the picture and the text, but ignores the detailed information of the pedestrians in the picture, so that the specific similarity value between the samples cannot be obtained, and the problem of lack of supervision information .

Description

technical field [0001] The invention belongs to the field of vision technology, and in particular relates to a text-based pedestrian retrieval self-supervised visual representation learning system and method. Background technique [0002] Traditional text-based pedestrian retrieval models utilize two-part networks to extract image and text feature descriptions, respectively, and usually, a ternary loss function is used to supervise the learning of the network. This method has achieved good results, but there are still two disadvantages: [0003] First, existing networks only focus on the similarity between pictures and texts, but ignore the details of pedestrians in pictures, such as gender, clothing, and actions. This makes the learned visual features in the network less robust. Second, the loss function used in the currently proposed method utilizes the dataset as discrete variables labeled as 0 or 1. Given a set of image-text pairs, according to the dataset annotation,...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06V40/10G06V10/764G06V10/766G06V10/774G06V10/82G06F16/35G06N3/04G06N3/08
CPCG06F16/353G06N3/08G06V40/103G06N3/045G06F18/214G06F18/24
Inventor 高联丽樊凯旋宋井宽
Owner GUIZHOU UNIV
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