Image Captioning in News Report Scenario

Image Captioning in News Report Scenario

2024 | Tianrui Liu, Qi Cai, Changxin Xu, Bo Hong, Jize Xiong, Yuxin Qiao, Tsungwei Yang
This paper explores the application of image captioning in news reporting, particularly focusing on celebrity photographs. The authors propose a combined method to generate detailed and accurate captions that include the identities of celebrities in the images. The approach involves three main steps: image captioning, face recognition, and noun phrase (NP) chunk matching. 1. **Image Captioning**: A common encoder-decoder architecture is used to generate initial captions without specific names. 2. **Face Recognition**: MTCNN and ResNet are employed to detect and classify faces in the images. 3. **Noun Phrase Chunk Matching**: The generated captions are parsed, and NP chunks are replaced with the names of celebrities identified in the images. The paper discusses the challenges and limitations of the method, such as mediocre generation performance due to limited datasets and inaccurate NP chunk matching. Potential solutions include using more sophisticated multi-modality approaches, improving dataset quality, and considering the task jointly. The authors conclude that their pipeline can significantly enhance the accuracy and relevance of generated content, paving the way for more intelligent and automated news generation systems.This paper explores the application of image captioning in news reporting, particularly focusing on celebrity photographs. The authors propose a combined method to generate detailed and accurate captions that include the identities of celebrities in the images. The approach involves three main steps: image captioning, face recognition, and noun phrase (NP) chunk matching. 1. **Image Captioning**: A common encoder-decoder architecture is used to generate initial captions without specific names. 2. **Face Recognition**: MTCNN and ResNet are employed to detect and classify faces in the images. 3. **Noun Phrase Chunk Matching**: The generated captions are parsed, and NP chunks are replaced with the names of celebrities identified in the images. The paper discusses the challenges and limitations of the method, such as mediocre generation performance due to limited datasets and inaccurate NP chunk matching. Potential solutions include using more sophisticated multi-modality approaches, improving dataset quality, and considering the task jointly. The authors conclude that their pipeline can significantly enhance the accuracy and relevance of generated content, paving the way for more intelligent and automated news generation systems.
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Understanding Image Captioning in news report scenario