mlsanityData to 7 Oct 2026

PHOCNet: A Deep Convolutional Neural Network for Word Spotting in Handwritten Documents

arXiv 1604.00187 ↗First posted 1 Apr 2016cs.CVcited by 18

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Abstract (arXiv)

In recent years, deep convolutional neural networks have achieved state of the art performance in various computer vision task such as classification, detection or segmentation. Due to their outstanding performance, CNNs are more and more used in the field of document image analysis as well. In this work, we present a CNN architecture that is trained with the recently proposed PHOC representation. We show empirically that our CNN architecture is able to outperform state of the art results for various word spotting benchmarks while exhibiting short training and test times.

Key facts. Cited by 18 papers in the map (data through 7 Oct 2026). First posted on arXiv 1 Apr 2016.

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Citing papers per year: 2021: 4; 2022: 4; 2023: 3; 2024: 4; 2025: 1; 2026: 2.

18 papers.

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  1. 2022A Survey of Historical Document Image Datasetscited by 18
  2. 2024Best Practices for a Handwritten Text Recognition Systemcited by 17
  3. 2021Scene Text Retrieval via Joint Text Detection and Similarity Learningcited by 15
  4. 2021Asking questions on handwritten document collectionscited by 14
  5. 2024Towards End-to-End Explainable Facial Action Unit Recognition via Vision-Language Joint Learningcited by 9
  6. 2023Multi-Granularity Prediction with Learnable Fusion for Scene Text Recognitioncited by 7
  7. 2024Focus, Distinguish, and Prompt: Unleashing CLIP for Efficient and Flexible Scene Text Retrievalcited by 6
  8. 2022Recognition-free Question Answering on Handwritten Document Collectionscited by 3
  9. 2023ST-KeyS: Self-Supervised Transformer for Keyword Spotting in Historical Handwritten Documentscited by 3
  10. 2024Partial Scene Text Retrievalcited by 3
  11. 2021Pho(SC)-CTC -- A Hybrid Approach Towards Zero-shot Word Image Recognitioncited by 2
  12. 2022A Few Shot Multi-Representation Approach for N-gram Spotting in Historical Manuscriptscited by 2
6 more
  1. 2025PILOT: A Promptable Interleaved Layout-aware OCR Transformercited by 2
  2. 2021Learning to Rank Words: Optimizing Ranking Metrics for Word Spottingcited by 1
  3. 2023Keyword Spotting Simplified: A Segmentation-Free Approach using Character Counting and CTC re-scoringcited by 1
  4. 2022TextMatcher: Cross-Attentional Neural Network to Compare Image and Textcited by 0
  5. 2026Unsupervised Domain Adaptation for Symbol Spotting in Historical Encrypted Manuscriptscited by 0
  6. 2026HPMD: A Historical Persian Manuscript Dataset for Word Spotting with Line-Level Annotationcited by 0