Summary of Instructocr: Instruction Boosting Scene Text Spotting, by Chen Duan et al.
InstructOCR: Instruction Boosting Scene Text Spotting
by Chen Duan, Qianyi Jiang, Pei Fu, Jiamin Chen, Shengxi Li, Zining Wang, Shan Guo, Junfeng Luo
First submitted to arxiv on: 20 Dec 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper proposes InstructOCR, an innovative scene text spotting model that incorporates human language instructions to improve text understanding within images. The framework uses both text and image encoders during training and inference, along with meticulously designed instructions based on text attributes. This approach enables the model to interpret text more accurately and flexibly, achieving state-of-the-art results on widely used benchmarks. Furthermore, the proposed framework can be applied to scene text VQA tasks, significantly improving performance by 2.6% on TextVQA and 2.1% on ST-VQA datasets. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary InstructOCR is a new way to recognize text in pictures that uses human instructions to help it understand what it’s looking at. The model combines image and text information with special instructions designed just for recognizing text. This makes the model better at reading text in different situations. It even works well on harder tasks like answering questions about what’s in an image. |
Keywords
» Artificial intelligence » Inference
