Search Results for author: Yuning Du

Found 16 papers, 15 papers with code

DETRs Beat YOLOs on Real-time Object Detection

3 code implementations17 Apr 2023 Wenyu Lv, Shangliang Xu, Yian Zhao, Guanzhong Wang, Jinman Wei, Cheng Cui, Yuning Du, Qingqing Dang, Yi Liu

In this paper, we first analyze the influence of NMS in modern real-time object detectors on inference speed, and establish an end-to-end speed benchmark.

2D object detection object-detection +1

PP-StructureV2: A Stronger Document Analysis System

1 code implementation11 Oct 2022 Chenxia Li, Ruoyu Guo, Jun Zhou, Mengtao An, Yuning Du, Lingfeng Zhu, Yi Liu, Xiaoguang Hu, dianhai yu

For Table Recognition model, we utilize PP-LCNet, CSP-PAN and SLAHead to optimize the backbone module, feature fusion module and decoding module, respectively, which improved the table structure accuracy by 6\% with comparable inference speed.

Key Information Extraction Knowledge Distillation +2

PP-OCRv3: More Attempts for the Improvement of Ultra Lightweight OCR System

1 code implementation7 Jun 2022 Chenxia Li, Weiwei Liu, Ruoyu Guo, Xiaoting Yin, Kaitao Jiang, Yongkun Du, Yuning Du, Lingfeng Zhu, Baohua Lai, Xiaoguang Hu, dianhai yu, Yanjun Ma

For text recognizer, the base model is replaced from CRNN to SVTR, and we introduce lightweight text recognition network SVTR LCNet, guided training of CTC by attention, data augmentation strategy TextConAug, better pre-trained model by self-supervised TextRotNet, UDML, and UIM to accelerate the model and improve the effect.

Data Augmentation Optical Character Recognition (OCR)

SVTR: Scene Text Recognition with a Single Visual Model

1 code implementation30 Apr 2022 Yongkun Du, Zhineng Chen, Caiyan Jia, Xiaoting Yin, Tianlun Zheng, Chenxia Li, Yuning Du, Yu-Gang Jiang

Dominant scene text recognition models commonly contain two building blocks, a visual model for feature extraction and a sequence model for text transcription.

Scene Text Recognition

PP-YOLOE: An evolved version of YOLO

7 code implementations30 Mar 2022 Shangliang Xu, Xinxin Wang, Wenyu Lv, Qinyao Chang, Cheng Cui, Kaipeng Deng, Guanzhong Wang, Qingqing Dang, Shengyu Wei, Yuning Du, Baohua Lai

In this report, we present PP-YOLOE, an industrial state-of-the-art object detector with high performance and friendly deployment.

2D object detection Dense Object Detection +4

PP-LCNet: A Lightweight CPU Convolutional Neural Network

8 code implementations17 Sep 2021 Cheng Cui, Tingquan Gao, Shengyu Wei, Yuning Du, Ruoyu Guo, Shuilong Dong, Bin Lu, Ying Zhou, Xueying Lv, Qiwen Liu, Xiaoguang Hu, dianhai yu, Yanjun Ma

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.

Image Classification object-detection +2

HS-ResNet: Hierarchical-Split Block on Convolutional Neural Network

2 code implementations15 Oct 2020 Pengcheng Yuan, Shufei Lin, Cheng Cui, Yuning Du, Ruoyu Guo, Dongliang He, Errui Ding, Shumin Han

Moreover, Hierarchical-Split block is very flexible and efficient, which provides a large space of potential network architectures for different applications.

Image Classification Image Segmentation +4

PP-OCR: A Practical Ultra Lightweight OCR System

9 code implementations21 Sep 2020 Yuning Du, Chenxia Li, Ruoyu Guo, Xiaoting Yin, Weiwei Liu, Jun Zhou, Yifan Bai, Zilin Yu, Yehua Yang, Qingqing Dang, Haoshuang Wang

Meanwhile, several pre-trained models for the Chinese and English recognition are released, including a text detector (97K images are used), a direction classifier (600K images are used) as well as a text recognizer (17. 9M images are used).

Optical Character Recognition (OCR)

2nd Place and 2nd Place Solution to Kaggle Landmark Recognition andRetrieval Competition 2019

2 code implementations10 Jun 2019 Kaibing Chen, Cheng Cui, Yuning Du, Xianglong Meng, Hui Ren

We present a retrieval based system for landmark retrieval and recognition challenge. There are five parts in retrieval competition system, including feature extraction and matching to get candidates queue; database augmentation and query extension searching; reranking from recognition results and local feature matching.

Landmark Recognition Retrieval

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