Scene Text Detection is a task to detect text regions in the complex background and label them with bounding boxes.
Source: ContourNet: Taking a Further Step toward Accurate Arbitrary-shaped Scene Text Detection
Such a task is usually realized by matching a query text to the recognized words, outputted by an end-to-end scene text spotter.
In inference stage, the detection branch outputs the proposal refinement and the recognition branch predicts the transcript of the refined text region.
To address the severe domain distribution mismatch, we propose a synthetic-to-real domain adaptation method for scene text detection, which transfers knowledge from synthetic data (source domain) to real data (target domain).
ADVERSARIAL TEXT SCENE TEXT SCENE TEXT DETECTION UNSUPERVISED DOMAIN ADAPTATION
Arbitrary-shaped text detection is a challenging task due to the complex geometric layouts of texts such as large aspect ratios, various scales, random rotations and curve shapes.
Thus, unlike previous surveys in this field, the objectives of this survey are as follows: first, offering the reader not only a review on the recent advancement in scene text detection and recognition, but also presenting the results of conducting extensive experiments using a unified evaluation framework that assesses pre-trained models of the selected methods on challenging cases, and applies the same evaluation criteria on these techniques.
More specifically, we propose to perceive texts from three levels of feature representations, i. e., character-, word- and global-level, and then introduce a novel text representation fusion technique to help achieve robust arbitrary text detection.
Ranked #1 on
Scene Text Detection
on IC19-Art
We propose an unsupervised approach for sarcasm generation based on a non-sarcastic input sentence.
Then a novel Local Orthogonal Texture-aware Module (LOTM) models the local texture information of proposal features in two orthogonal directions and represents text region with a set of contour points.
Synthetic data has been a critical tool for training scene text detection and recognition models.
IMAGE GENERATION SCENE TEXT SCENE TEXT DETECTION SCENE TEXT RECOGNITION
Our contributions are three-fold: 1) For the first time, we adaptively fit arbitrarily-shaped text by a parameterized Bezier curve.