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20192026
most citedFC2RN: A Fully Convolutional Corner Refinement Network for Accurate Multi-Oriented Scene Text Detection

6 citations · 12 across the 7 of their papers we have counts for

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11 papers · 1 filter

cs.CV2026

Embedding Rotation Invariance for Provable Multi-Oriented Scene Text Recognition

Zhibin Ma, Pengwen Dai, Yi Liu +3

Multi-oriented text is ubiquitous in real-world scenes and remains a major challenge for scene text recognition (STR). Existing rotation-aware methods explicitly estimate text orie…

cs.CV2026

Towards Training-Free Scene Text Editing

Yubo Li, Xugong Qin, Peng Zhang +3

Scene text editing seeks to modify textual content in natural images while maintaining visual realism and semantic consistency. Existing methods often require task-specific trainin…

cs.CV2024

Focus, Distinguish, and Prompt: Unleashing CLIP for Efficient and Flexible Scene Text Retrieval

Gangyan Zeng, Yuan Zhang, Jin Wei +5

Scene text retrieval aims to find all images containing the query text from an image gallery. Current efforts tend to adopt an Optical Character Recognition (OCR) pipeline, which r…

cs.CV2023★ 1 cited

Towards Robust Real-Time Scene Text Detection: From Semantic to Instance Representation Learning

Xugong Qin, Pengyuan Lyu, Chengquan Zhang +5

Due to the flexible representation of arbitrary-shaped scene text and simple pipeline, bottom-up segmentation-based methods begin to be mainstream in real-time scene text detection…

cs.CV2022

UNITS: Unsupervised Intermediate Training Stage for Scene Text Detection

Youhui Guo, Yu Zhou, Xugong Qin +2

Recent scene text detection methods are almost based on deep learning and data-driven. Synthetic data is commonly adopted for pre-training due to expensive annotation cost. However…

cs.CV2021★ 1 cited

Which and Where to Focus: A Simple yet Accurate Framework for Arbitrary-Shaped Nearby Text Detection in Scene Images

Youhui Guo, Yu Zhou, Xugong Qin +1

Scene text detection has drawn the close attention of researchers. Though many methods have been proposed for horizontal and oriented texts, previous methods may not perform well w…