212 citations · 480 across the 34 of their papers we have counts for
35 papers · 1 filter
Privacy-Preserving Biometric Verification with Handwritten Random Digit String
Peirong Zhang, Yuliang Liu, Songxuan Lai +2
Handwriting verification has stood as a steadfast identity authentication method for decades. However, this technique risks potential privacy breaches due to the inclusion of perso…
Turning a CLIP Model into a Scene Text Spotter
Wenwen Yu, Yuliang Liu, Xingkui Zhu +3
We exploit the potential of the large-scale Contrastive Language-Image Pretraining (CLIP) model to enhance scene text detection and spotting tasks, transforming it into a robust ba…
ESTextSpotter: Towards Better Scene Text Spotting with Explicit Synergy in Transformer
Mingxin Huang, Jiaxin Zhang, Dezhi Peng +5
In recent years, end-to-end scene text spotting approaches are evolving to the Transformer-based framework. While previous studies have shown the crucial importance of the intrinsi…
Box-DETR: Understanding and Boxing Conditional Spatial Queries
Wenze Liu, Hao Lu, Yuliang Liu +1
Conditional spatial queries are recently introduced into DEtection TRansformer (DETR) to accelerate convergence. In DAB-DETR, such queries are modulated by the so-called conditiona…
On Point Affiliation in Feature Upsampling
Wenze Liu, Hao Lu, Yuliang Liu +1
We introduce the notion of point affiliation into feature upsampling. By abstracting a feature map into non-overlapped semantic clusters formed by points of identical semantic mean…
Looking and Listening: Audio Guided Text Recognition
Wenwen Yu, Mingyu Liu, Biao Yang +5
Text recognition in the wild is a long-standing problem in computer vision. Driven by end-to-end deep learning, recent studies suggest vision and language processing are effective…
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…
ViTEraser: Harnessing the Power of Vision Transformers for Scene Text Removal with SegMIM Pretraining
Dezhi Peng, Chongyu Liu, Yuliang Liu +1
Scene text removal (STR) aims at replacing text strokes in natural scenes with visually coherent backgrounds. Recent STR approaches rely on iterative refinements or explicit text m…
ICDAR 2023 Competition on Reading the Seal Title
Wenwen Yu, Mingyu Liu, Mingrui Chen +5
Reading seal title text is a challenging task due to the variable shapes of seals, curved text, background noise, and overlapped text. However, this important element is commonly f…
Turning a CLIP Model into a Scene Text Detector
Wenwen Yu, Yuliang Liu, Wei Hua +3
The recent large-scale Contrastive Language-Image Pretraining (CLIP) model has shown great potential in various downstream tasks via leveraging the pretrained vision and language k…
Accountable Textual-Visual Chat Learns to Reject Human Instructions in Image Re-creation
Zhiwei Zhang, Yuliang Liu
The recent success of ChatGPT and GPT-4 has drawn widespread attention to multimodal dialogue systems. However, there is a lack of datasets in the academic community that can effec…
SPTS v2: Single-Point Scene Text Spotting
Yuliang Liu, Jiaxin Zhang, Dezhi Peng +8
End-to-end scene text spotting has made significant progress due to its intrinsic synergy between text detection and recognition. Previous methods commonly regard manual annotation…
MSDS: A Large-Scale Chinese Signature and Token Digit String Dataset for Handwriting Verification
Peirong Zhang, Jiajia Jiang, Yuliang Liu +1
Although online handwriting verification has made great progress recently, the verification performances are still far behind the real usage owing to the small scale of the dataset…
SAPA: Similarity-Aware Point Affiliation for Feature Upsampling
Hao Lu, Wenze Liu, Zixuan Ye +3
We introduce point affiliation into feature upsampling, a notion that describes the affiliation of each upsampled point to a semantic cluster formed by local decoder feature points…
PageNet: Towards End-to-End Weakly Supervised Page-Level Handwritten Chinese Text Recognition
Dezhi Peng, Lianwen Jin, Yuliang Liu +2
Handwritten Chinese text recognition (HCTR) has been an active research topic for decades. However, most previous studies solely focus on the recognition of cropped text line image…
Don't Forget Me: Accurate Background Recovery for Text Removal via Modeling Local-Global Context
Chongyu Liu, Lianwen Jin, Yuliang Liu +4
Text removal has attracted increasingly attention due to its various applications on privacy protection, document restoration, and text editing. It has shown significant progress w…
SwinTextSpotter: Scene Text Spotting via Better Synergy between Text Detection and Text Recognition
Mingxin Huang, Yuliang Liu, Zhenghao Peng +6
End-to-end scene text spotting has attracted great attention in recent years due to the success of excavating the intrinsic synergy of the scene text detection and recognition. How…
SPTS: Single-Point Text Spotting
Dezhi Peng, Xinyu Wang, Yuliang Liu +9
Existing scene text spotting (i.e., end-to-end text detection and recognition) methods rely on costly bounding box annotations (e.g., text-line, word-level, or character-level boun…
ICDAR 2021 Competition on Integrated Circuit Text Spotting and Aesthetic Assessment
Chun Chet Ng, Akmalul Khairi Bin Nazaruddin, Yeong Khang Lee +6
With hundreds of thousands of electronic chip components are being manufactured every day, chip manufacturers have seen an increasing demand in seeking a more efficient and effecti…
ABCNet v2: Adaptive Bezier-Curve Network for Real-time End-to-end Text Spotting
Yuliang Liu, Chunhua Shen, Lianwen Jin +4
End-to-end text-spotting, which aims to integrate detection and recognition in a unified framework, has attracted increasing attention due to its simplicity of the two complimentar…
Structured Multimodal Attentions for TextVQA
Chenyu Gao, Qi Zhu, Peng Wang +4
In this paper, we propose an end-to-end structured multimodal attention (SMA) neural network to mainly solve the first two issues above. SMA first uses a structural graph represent…
On the General Value of Evidence, and Bilingual Scene-Text Visual Question Answering
Xinyu Wang, Yuliang Liu, Chunhua Shen +6
Visual Question Answering (VQA) methods have made incredible progress, but suffer from a failure to generalize. This is visible in the fact that they are vulnerable to learning coi…
ABCNet: Real-time Scene Text Spotting with Adaptive Bezier-Curve Network
Yuliang Liu, Hao Chen, Chunhua Shen +3
Scene text detection and recognition has received increasing research attention. Existing methods can be roughly categorized into two groups: character-based and segmentation-based…
Separating Content from Style Using Adversarial Learning for Recognizing Text in the Wild
Canjie Luo, Qingxiang Lin, Yuliang Liu +2
We propose to improve text recognition from a new perspective by separating the text content from complex backgrounds. As vanilla GANs are not sufficiently robust to generate seque…