Search Results for author: Ya Guo

Found 8 papers, 2 papers with code

Rethinking the Evaluation of Pre-trained Text-and-Layout Models from an Entity-Centric Perspective

no code implementations4 Feb 2024 Chong Zhang, Yixi Zhao, Chenshu Yuan, Yi Tu, Ya Guo, Qi Zhang

Therefore, we claim the necessary standards for an ideal benchmark to evaluate the information extraction ability of PTLMs.

Entity Linking

Reading Order Matters: Information Extraction from Visually-rich Documents by Token Path Prediction

2 code implementations17 Oct 2023 Chong Zhang, Ya Guo, Yi Tu, Huan Chen, Jinyang Tang, Huijia Zhu, Qi Zhang, Tao Gui

However, BIO-tagging scheme relies on the correct order of model inputs, which is not guaranteed in real-world NER on scanned VrDs where text are recognized and arranged by OCR systems.

Entity Linking Key Information Extraction +9

LayoutMask: Enhance Text-Layout Interaction in Multi-modal Pre-training for Document Understanding

no code implementations30 May 2023 Yi Tu, Ya Guo, Huan Chen, Jinyang Tang

LayoutMask can enhance the interactions between text and layout modalities in a unified model and produce adaptive and robust multi-modal representations for downstream tasks.

Document Image Classification document understanding +7

Unsupervised domain adaptation semantic segmentation of high-resolution remote sensing imagery with invariant domain-level prototype memory

1 code implementation16 Aug 2022 Jingru Zhu, Ya Guo, Geng Sun, Libo Yang, Min Deng, Jie Chen

This study proposes a novel unsupervised domain adaptation semantic segmentation network (MemoryAdaptNet) for the semantic segmentation of HRS imagery.

Pseudo Label Pseudo Label Filtering +3

A comprehensive benchmark analysis for sand dust image reconstruction

no code implementations7 Feb 2022 Yazhong Si, Fan Yang, Ya Guo, Wei zhang, Yipu Yang

In this paper, we presented a comprehensive perceptual study and analysis of real-world sand dust images, then constructed a Sand-dust Image Reconstruction Benchmark (SIRB) for training Convolutional Neural Networks (CNNs) and evaluating algorithms performance.

Image Enhancement Image Reconstruction

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