Scene Text Detection
91 papers with code • 9 benchmarks • 15 datasets
Scene Text Detection is a computer vision task that involves automatically identifying and localizing text within natural images or videos. The goal of scene text detection is to develop algorithms that can robustly detect and and label text with bounding boxes in uncontrolled and complex environments, such as street signs, billboards, or license plates.
Source: ContourNet: Taking a Further Step toward Accurate Arbitrary-shaped Scene Text Detection
Benchmarks
These leaderboards are used to track progress in Scene Text Detection
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Libraries
Use these libraries to find Scene Text Detection models and implementationsDatasets
ICDAR 2013
Total-Text
MSRA-TD500
COCO-Text
ICDAR 2015
SCUT-CTW1500
TextOCR
ICDAR 2017
RCTW-17
Chinese Text in the Wild
Latest papers with no code
MENTOR: Multilingual tExt detectioN TOward leaRning by analogy
Text detection is frequently used in vision-based mobile robots when they need to interpret texts in their surroundings to perform a given task.
ODM: A Text-Image Further Alignment Pre-training Approach for Scene Text Detection and Spotting
With ODM, we achieve better alignment between text and OCR-Text and enable pre-trained models to adapt to the complex and diverse styles of scene text detection and spotting tasks.
CPN: Complementary Proposal Network for Unconstrained Text Detection
Existing methods for scene text detection can be divided into two paradigms: segmentation-based and anchor-based.
EK-Net:Real-time Scene Text Detection with Expand Kernel Distance
Recently, scene text detection has received significant attention due to its wide application.
Text Region Multiple Information Perception Network for Scene Text Detection
Segmentation-based scene text detection algorithms can handle arbitrary shape scene texts and have strong robustness and adaptability, so it has attracted wide attention.
BPDO:Boundary Points Dynamic Optimization for Arbitrary Shape Scene Text Detection
Arbitrary shape scene text detection is of great importance in scene understanding tasks.
Research on Multilingual Natural Scene Text Detection Algorithm
Natural scene text detection is a significant challenge in computer vision, with tremendous potential applications in multilingual, diverse, and complex text scenarios.
Bridging Synthetic and Real Worlds for Pre-training Scene Text Detectors
Existing scene text detection methods typically rely on extensive real data for training.
Enhancing Scene Text Detectors with Realistic Text Image Synthesis Using Diffusion Models
We contend that one main limitation of existing generation methods is the insufficient integration of foreground text with the background.
Towards Robust Real-Time Scene Text Detection: From Semantic to Instance Representation Learning
Different from existing methods which integrate multiple-granularity features or multiple outputs, we resort to the perspective of representation learning in which auxiliary tasks are utilized to enable the encoder to jointly learn robust features with the main task of per-pixel classification during optimization.
