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Dec 24, 2023 · Image-text matching based on knowledge features: Traditional image-text matching only considers the features of images and texts, so it is ...
To solve this issue, we propose a Location Attention Knowledge Embedding (LAKE) model to improve the consensus knowledge utilization by inferring the location ...
Feb 27, 2024 · In order to enhance the representation ability in two-stream models, in this paper, we propose a novel Multi-View Attention Model (MVAM), which ...
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The Paper List of Large Multi-Modality Model, Parameter-Efficient Finetuning, Vision-Language Pretraining, Conventional Image-Text Matching for Preliminary ...
Mar 5, 2023 · The position feature allows the model to measure the importance of the object region based on the positional cues, thereby focusing on the ...
In this paper, we propose an Attentional Generative Adversarial Network (AttnGAN) that allows attention-driven, multi-stage refinement for fine-grained text-to- ...
Apr 28, 2024 · Abstract—Image-text matching remains a challenging task due to heterogeneous semantic diversity across modalities and.
Nov 9, 2023 · A text embedding is a piece of text projected into a high-dimensional latent space. The position of our text in this space is a vector, a long ...
Jan 22, 2024 · This article proposed a knowledge embedding learning model, which incorporates a graph attention mechanism to integrate key node information. It ...
To the best of our knowledge, this is the first framework that performs image-text matching on hetero- geneous visual and textual graphs. (2) To the best of our.