Methods › Computer Vision › Vision and Language Pre-Trained Models › XGPT
XGPT
Introduced by Qiaolin Xia et al. in XGPT: Cross-modal Generative Pre-Training for Image Captioning
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
XGPT is a method of cross-modal generative pre-training for image captioning designed to pre-train text-to-image caption generators through three novel generation tasks, including image-conditioned masked language modeling (IMLM), image-conditioned denoising autoencoding (IDA), and text-conditioned image feature generation (TIGF). The pre-trained XGPT can be fine-tuned without any task-specific architecture modifications and build strong image captioning models.
Papers archive 2025-07-28
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XGPT: Cross-modal Generative Pre-Training for Image Captioning 3 Mar 2020 · 0 repositories · arXiv:2003.01473
Tasks archive 2025-07-28
11 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
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