136 citations · 574 across the 14 of their papers we have counts for
14 papers
ICDAR 2023 Competition on Structured Text Extraction from Visually-Rich Document Images
Wenwen Yu, Chengquan Zhang, Haoyu Cao +24
Structured text extraction is one of the most valuable and challenging application directions in the field of Document AI. However, the scenarios of past benchmarks are limited, an…
PP-YOLOE-R: An Efficient Anchor-Free Rotated Object Detector
Xinxin Wang, Guanzhong Wang, Qingqing Dang +3
Arbitrary-oriented object detection is a fundamental task in visual scenes involving aerial images and scene text. In this report, we present PP-YOLOE-R, an efficient anchor-free r…
PP-StructureV2: A Stronger Document Analysis System
Chenxia Li, Ruoyu Guo, Jun Zhou +6
A large amount of document data exists in unstructured form such as raw images without any text information. Designing a practical document image analysis system is a meaningful bu…
PP-OCRv3: More Attempts for the Improvement of Ultra Lightweight OCR System
Chenxia Li, Weiwei Liu, Ruoyu Guo +9
Optical character recognition (OCR) technology has been widely used in various scenes, as shown in Figure 1. Designing a practical OCR system is still a meaningful but challenging…
PaddleSpeech: An Easy-to-Use All-in-One Speech Toolkit
Hui Zhang, Tian Yuan, Junkun Chen +10
PaddleSpeech is an open-source all-in-one speech toolkit. It aims at facilitating the development and research of speech processing technologies by providing an easy-to-use command…
PP-Matting: High-Accuracy Natural Image Matting
Guowei Chen, Yi Liu, Jian Wang +11
Natural image matting is a fundamental and challenging computer vision task. It has many applications in image editing and composition. Recently, deep learning-based approaches hav…
PP-LiteSeg: A Superior Real-Time Semantic Segmentation Model
Juncai Peng, Yi Liu, Shiyu Tang +13
Real-world applications have high demands for semantic segmentation methods. Although semantic segmentation has made remarkable leap-forwards with deep learning, the performance of…
PP-PicoDet: A Better Real-Time Object Detector on Mobile Devices
Guanghua Yu, Qinyao Chang, Wenyu Lv +12
The better accuracy and efficiency trade-off has been a challenging problem in object detection. In this work, we are dedicated to studying key optimizations and neural network arc…
PP-ShiTu: A Practical Lightweight Image Recognition System
Shengyu Wei, Ruoyu Guo, Cheng Cui +10
In recent years, image recognition applications have developed rapidly. A large number of studies and techniques have emerged in different fields, such as face recognition, pedestr…
PP-OCRv2: Bag of Tricks for Ultra Lightweight OCR System
Yuning Du, Chenxia Li, Ruoyu Guo +9
Optical Character Recognition (OCR) systems have been widely used in various of application scenarios. Designing an OCR system is still a challenging task. In previous work, we pro…
PP-LCNet: A Lightweight CPU Convolutional Neural Network
Cheng Cui, Tingquan Gao, Shengyu Wei +10
We propose a lightweight CPU network based on the MKLDNN acceleration strategy, named PP-LCNet, which improves the performance of lightweight models on multiple tasks. This paper l…
PP-YOLOv2: A Practical Object Detector
Xin Huang, Xinxin Wang, Wenyu Lv +10
Being effective and efficient is essential to an object detector for practical use. To meet these two concerns, we comprehensively evaluate a collection of existing refinements to…
Beyond Self-Supervision: A Simple Yet Effective Network Distillation Alternative to Improve Backbones
Cheng Cui, Ruoyu Guo, Yuning Du +10
Recently, research efforts have been concentrated on revealing how pre-trained model makes a difference in neural network performance. Self-supervision and semi-supervised learning…
Multi-channel Encoder for Neural Machine Translation
Hao Xiong, Zhongjun He, Xiaoguang Hu +1
Attention-based Encoder-Decoder has the effective architecture for neural machine translation (NMT), which typically relies on recurrent neural networks (RNN) to build the blocks t…