39l.jpg | 4K |

This paper introduces a first-of-its-kind benchmark for fine-grained document retrieval in natural scenes. It includes a dataset of 41,000 document images (where files like 39l.jpg are part of the image corpus) paired with over 200,000 queries .

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The study highlights that OCR-free models perform better when queries involve visual, non-text elements, and that models pre-trained on image-text contrastive learning tasks (like CLIP ) show superior accuracy. Other Potential Matches Other Potential Matches Recent papers like Monkey: Image

Recent papers like Monkey: Image Resolution and Text Label Are Important Things for CVPR 2024 use high-resolution image sets to improve visual understanding in Large Language Models. 39l.jpg

(PDF) Image Matching across Wide Baselines: From Paper to Practice

Some researchers use these specific filenames in benchmarks for Image Matching across Wide Baselines to test how models handle different perspectives of the same object.