75 citations · 296 across the 13 of their papers we have counts for
14 papers
ARTS: Eliminating Inconsistency between Text Detection and Recognition with Auto-Rectification Text Spotter
Humen Zhong, Jun Tang, Wenhai Wang +3
Recent approaches for end-to-end text spotting have achieved promising results. However, most of the current spotters were plagued by the inconsistency problem between text detecti…
PAN++: Towards Efficient and Accurate End-to-End Spotting of Arbitrarily-Shaped Text
Wenhai Wang, Enze Xie, Xiang Li +5
Scene text detection and recognition have been well explored in the past few years. Despite the progress, efficient and accurate end-to-end spotting of arbitrarily-shaped text rema…
Towards Ultra-Resolution Neural Style Transfer via Thumbnail Instance Normalization
Zhe Chen, Wenhai Wang, Enze Xie +2
We present an extremely simple Ultra-Resolution Style Transfer framework, termed URST, to flexibly process arbitrary high-resolution images (e.g., 10000x10000 pixels) style transfe…
Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutions
Wenhai Wang, Enze Xie, Xiang Li +6
Although using convolutional neural networks (CNNs) as backbones achieves great successes in computer vision, this work investigates a simple backbone network useful for many dense…
Frequency Consistent Adaptation for Real World Super Resolution
Xiaozhong Ji, Guangpin Tao, Yun Cao +5
Recent deep-learning based Super-Resolution (SR) methods have achieved remarkable performance on images with known degradation. However, these methods always fail in real-world sce…
AE TextSpotter: Learning Visual and Linguistic Representation for Ambiguous Text Spotting
Wenhai Wang, Xuebo Liu, Xiaozhong Ji +6
Scene text spotting aims to detect and recognize the entire word or sentence with multiple characters in natural images. It is still challenging because ambiguity often occurs when…
Channel Relationship Prediction with Forget-Update Module for Few-shot Classification
Minglei Yuan, Cunhao Cai, Tong Lu
In this paper, we proposed a pipeline for inferring the relationship of each class in support set and a query sample using forget-update module. We first propose a novel architectu…
A New Unified Method for Detecting Text from Marathon Runners and Sports Players in Video
Sauradip Nag, Palaiahnakote Shivakumara, Umapada Pal +2
Detecting text located on the torsos of marathon runners and sports players in video is a challenging issue due to poor quality and adverse effects caused by flexible/colorful clot…
TEINet: Towards an Efficient Architecture for Video Recognition
Zhaoyang Liu, Donghao Luo, Yabiao Wang +6
Efficiency is an important issue in designing video architectures for action recognition. 3D CNNs have witnessed remarkable progress in action recognition from videos. However, com…
Efficient and Accurate Arbitrary-Shaped Text Detection with Pixel Aggregation Network
Wenhai Wang, Enze Xie, Xiaoge Song +5
Scene text detection, an important step of scene text reading systems, has witnessed rapid development with convolutional neural networks. Nonetheless, two main challenges still ex…
Shape Robust Text Detection with Progressive Scale Expansion Network
Wenhai Wang, Enze Xie, Xiang Li +4
Scene text detection has witnessed rapid progress especially with the recent development of convolutional neural networks. However, there still exists two challenges which prevent…
A New COLD Feature based Handwriting Analysis for Ethnicity/Nationality Identification
Sauradip Nag, Palaiahnakote Shivakumara, Wu Yirui +2
Identifying crime for forensic investigating teams when crimes involve people of different nationals is challenging. This paper proposes a new method for ethnicity (nationality) id…
Shape Robust Text Detection with Progressive Scale Expansion Network
Xiang Li, Wenhai Wang, Wenbo Hou +3
The challenges of shape robust text detection lie in two aspects: 1) most existing quadrangular bounding box based detectors are difficult to locate texts with arbitrary shapes, wh…
Mixed Link Networks
Wenhai Wang, Xiang Li, Jian Yang +1
Basing on the analysis by revealing the equivalence of modern networks, we find that both ResNet and DenseNet are essentially derived from the same "dense topology", yet they only…