Text Matching
146 papers with code • 0 benchmarks • 7 datasets
Matching a target text to a source text based on their meaning.
Benchmarks
These leaderboards are used to track progress in Text Matching
MedICaT
DuLeMon
Most implemented papers
AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks
taoxugit/AttnGAN
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CVPR 2018
In this paper, we propose an Attentional Generative Adversarial Network (AttnGAN) that allows attention-driven, multi-stage refinement for fine-grained text-to-image generation.
Text Matching as Image Recognition
An effective way is to extract meaningful matching patterns from words, phrases, and sentences to produce the matching score.
UNITER: UNiversal Image-TExt Representation Learning
ChenRocks/UNITER
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ECCV 2020
Different from previous work that applies joint random masking to both modalities, we use conditional masking on pre-training tasks (i. e., masked language/region modeling is conditioned on full observation of image/text).
Knowledge Guided Text Retrieval and Reading for Open Domain Question Answering
We introduce an approach for open-domain question answering (QA) that retrieves and reads a passage graph, where vertices are passages of text and edges represent relationships that are derived from an external knowledge base or co-occurrence in the same article.
Stacked Cross Attention for Image-Text Matching
Prior work either simply aggregates the similarity of all possible pairs of regions and words without attending differentially to more and less important words or regions, or uses a multi-step attentional process to capture limited number of semantic alignments which is less interpretable.
Fine-grained Video-Text Retrieval with Hierarchical Graph Reasoning
CryhanFang/CLIP2Video
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CVPR 2020
To improve fine-grained video-text retrieval, we propose a Hierarchical Graph Reasoning (HGR) model, which decomposes video-text matching into global-to-local levels.
Simple and Effective Text Matching with Richer Alignment Features
hitvoice/RE2
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ACL 2019
In this paper, we present a fast and strong neural approach for general purpose text matching applications.
DF-GAN: A Simple and Effective Baseline for Text-to-Image Synthesis
To these ends, we propose a simpler but more effective Deep Fusion Generative Adversarial Networks (DF-GAN).
Dual Attention Networks for Multimodal Reasoning and Matching
iammrhelo/pytorch-vqa-dan
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CVPR 2017
We propose Dual Attention Networks (DANs) which jointly leverage visual and textual attention mechanisms to capture fine-grained interplay between vision and language.
Matching Images and Text with Multi-modal Tensor Fusion and Re-ranking
Wangt-CN/MTFN-RR-PyTorch-Code
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We propose a novel framework that achieves remarkable matching performance with acceptable model complexity.
