Papers with image captioning approaches
DeltaNet: Conditional Medical Report Generation for COVID-19 Diagnosis (2022.coling-1)
Copied to clipboard
Xian Wu, Shuxin Yang, Zhaopeng Qiu, Shen Ge, Yangtian Yan, Xingwang Wu, Yefeng Zheng, S. Kevin Zhou, Li Xiao
| Challenge: | X-ray and CT are the gold standard for COVID-19 diagnosis and treatment . however, due to the excessive number of patients, writing reports becomes a heavy burden for radiologists. |
| Approach: | They propose to use X-ray and CT to generate medical reports automatically . they evaluate DeltaNet on a COVID-19 dataset, where it outperforms state-of-the-art approaches . |
| Outcome: | The proposed system outperforms state-of-the-art methods on a COVID-19 dataset. |
Entity-aware Image Caption Generation (D18-1)
Copied to clipboard
| Challenge: | Existing image captioning approaches generate generic descriptions of visual content and ignore background information. |
| Approach: | They propose a task which generates informative image captions using images and hashtags as input. |
| Outcome: | The proposed model outperforms unimodal baselines significantly with evaluation metrics on a dataset from Flickr. |
Cross-Modal Similarity-Based Curriculum Learning for Image Captioning (2022.emnlp-main)
Copied to clipboard
| Challenge: | Existing image captioning approaches treat image-caption pairs indistinctly without considering the differences in their learning difficulties. |
| Approach: | They propose a pretrained vision–language model that measures cross-modal similarity and a model that uses cross-module similarity to measure the difficulty of captioning. |
| Outcome: | The proposed model achieves superior performance and competitive convergence speed to baselines without incurring additional training costs. |
Replace and Report: NLP Assisted Radiology Report Generation (2023.findings-acl)
Copied to clipboard
| Challenge: | Clinical practice frequently uses medical imaging for diagnosis and treatment. |
| Approach: | They propose a template-based approach to generate radiology reports from radiographs . they use multilabel image classifiers to generate tags, pathological descriptions from tags . |
| Outcome: | The proposed method improves on the most popular radiology report datasets. |