Papers › PromptCap: Prompt-Guided Task-Aware Image Captioning
PromptCap: Prompt-Guided Task-Aware Image Captioning
Yushi Hu, Hang Hua, Zhengyuan Yang, Weijia Shi, Noah A Smith, Jiebo Luo
Knowledge-based visual question answering (VQA) involves questions that require world knowledge beyond the image to yield the correct answer. Large language models (LMs) like GPT-3 are particularly helpful for this task because of their strong knowledge retrieval and reasoning capabilities. To enable LM to understand images, prior work uses a captioning model to convert images into text. However, when summarizing an image in a single caption sentence, which visual entities to describe are often underspecified. Generic image captions often miss visual details essential for the LM to answer visual questions correctly. To address this challenge, we propose PromptCap (Prompt-guided image Captioning), a captioning model designed to serve as a better connector between images and black-box LMs. Different from generic captions, PromptCap takes a natural-language prompt to control the visual entities to describe in the generated caption. The prompt contains a question that the caption should aid in answering. To avoid extra annotation, PromptCap is trained by examples synthesized with GPT-3 and existing datasets. We demonstrate PromptCap's effectiveness on an existing pipeline in which GPT-3 is prompted with image captions to carry out VQA. PromptCap outperforms generic captions by a large margin and achieves state-of-the-art accuracy on knowledge-based VQA tasks (60.4% on OK-VQA and 59.6% on A-OKVQA). Zero-shot results on WebQA show that PromptCap generalizes well to unseen domains.
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Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Visual Question Answering | TextVQA test-standard | PromptCap | overall | 51.80 | #1 of 1 | Archive leaderboard | report |
| Visual Question Answering (VQA) | A-OKVQA | PromptCap | DA VQA Score | 59.6 | #4 of 15 | Archive leaderboard | report |
| Visual Question Answering (VQA) | A-OKVQA | PromptCap | MC Accuracy | 73.2 | #4 of 15 | Archive leaderboard | report |
| Visual Question Answering (VQA) | OK-VQA | PromptCap | Accuracy | 60.4 | #8 of 37 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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