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Found 11 papers, 4 papers with code
Detect-Order-Construct: A Tree Construction based Approach for Hierarchical Document Structure Analysis
Our end-to-end system achieves state-of-the-art performance on two large-scale document layout analysis datasets (PubLayNet and DocLayNet), a high-quality hierarchical document structure reconstruction dataset (HRDoc), and our Comp-HRDoc benchmark.
Dynamic Relation Transformer for Contextual Text Block Detection
Contextual Text Block Detection (CTBD) is the task of identifying coherent text blocks within the complexity of natural scenes.
UniVIE: A Unified Label Space Approach to Visual Information Extraction from Form-like Documents
This unified approach allows for the definition of various relation types and effectively tackles hierarchical relationships in form-like documents.
Exploring Predicate Visual Context in Detecting Human-Object Interactions
Recently, the DETR framework has emerged as the dominant approach for human--object interaction (HOI) research.
Ranked #2 on
Human-Object Interaction Detection
on HICO-DET
A Question-Answering Approach to Key Value Pair Extraction from Form-like Document Images
In this paper, we present a new question-answering (QA) based key-value pair extraction approach, called KVPFormer, to robustly extracting key-value relationships between entities from form-like document images.
ViBERTgrid: A Jointly Trained Multi-Modal 2D Document Representation for Key Information Extraction from Documents
In this paper, we propose a new multi-modal backbone network by concatenating a BERTgrid to an intermediate layer of a CNN model, where the input of CNN is a document image and the BERTgrid is a grid of word embeddings, to generate a more powerful grid-based document representation, named ViBERTgrid.
ReLaText: Exploiting Visual Relationships for Arbitrary-Shaped Scene Text Detection with Graph Convolutional Networks
The key idea is to decompose text detection into two subproblems, namely detection of text primitives and prediction of link relationships between nearby text primitive pairs.
Mask R-CNN with Pyramid Attention Network for Scene Text Detection
In this paper, we present a new Mask R-CNN based text detection approach which can robustly detect multi-oriented and curved text from natural scene images in a unified manner.
Ranked #6 on
Scene Text Detection
on SCUT-CTW1500
An Anchor-Free Region Proposal Network for Faster R-CNN based Text Detection Approaches
The anchor mechanism of Faster R-CNN and SSD framework is considered not effective enough to scene text detection, which can be attributed to its IoU based matching criterion between anchors and ground-truth boxes.
DeepText: A Unified Framework for Text Proposal Generation and Text Detection in Natural Images
In this paper, we develop a novel unified framework called DeepText for text region proposal generation and text detection in natural images via a fully convolutional neural network (CNN).
High Performance Offline Handwritten Chinese Character Recognition Using GoogLeNet and Directional Feature Maps
We design a streamlined version of GoogLeNet [13], which was original proposed for image classification in recent years with very deep architecture, for HCCR (denoted as HCCR-GoogLeNet).
Image Classification
Offline Handwritten Chinese Character Recognition
