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Canjie Luo

7 accepted papers

2022

Don’t Forget Me: Accurate Background Recovery for Text Removal via Modeling Local-Global Context

ECCV 2022poster

"Text removal has attracted increasingly attention due to its various applications on privacy protection, document restoration, and text editing. It has shown significant progress with deep neural network. However, most of the existing methods often generate inconsistent results for complex backgrou…

2022

Look Closer To Supervise Better: One-Shot Font Generation via Component-Based Discriminator

CVPR 2022oral

Automatic font generation remains a challenging research issue due to the large amounts of characters with complicated structures. Typically, only a few samples can serve as the style/content reference (termed few-shot learning), which further increases the difficulty to preserve local style pattern…

Cited by 72PDFcodeScholar
2022

SimAN: Exploring Self-Supervised Representation Learning of Scene Text via Similarity-Aware Normalization

CVPR 2022poster

Recently self-supervised representation learning has drawn considerable attention from the scene text recognition community. Different from previous studies using contrastive learning, we tackle the issue from an alternative perspective, i.e., by formulating the representation learning scheme in a g…

Cited by 37PDFcodeScholar
2021

Implicit Feature Alignment: Learn To Convert Text Recognizer to Text Spotter

CVPR 2021poster

Text recognition is a popular research subject with many associated challenges. Despite the considerable progress made in recent years, the text recognition task itself is still constrained to solve the problem of reading cropped line text images and serves as a subtask of optical character recognit…

Cited by 16PDFcodeScholar
2020

Learn to Augment: Joint Data Augmentation and Network Optimization for Text Recognition

CVPR 2020poster

Handwritten text and scene text suffer from various shapes and distorted patterns. Thus training a robust recognition model requires a large amount of data to cover diversity as much as possible. In contrast to data collection and annotation, data augmentation is a low cost way. In this paper, we pr…

Cited by 116PDFcodeScholar
2020

On the General Value of Evidence, and Bilingual Scene-Text Visual Question Answering

CVPR 2020poster

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 coincidental correlations in the data rather than deeper relations between image content and ideas expressed in language. W…

Cited by 126PDFScholar
2019

Tightness-Aware Evaluation Protocol for Scene Text Detection

CVPR 2019poster

Evaluation protocols play key role in the developmental progress of text detection methods. There are strict requirements to ensure that the evaluation methods are fair, objective and reasonable. However, existing metrics exhibit some obvious drawbacks: 1) They are not goal-oriented; 2) they cannot…

Cited by 42PDFcodeScholar