Papers › Vision Transformer Based Model for Describing a Set of Images as a Story
Vision Transformer Based Model for Describing a Set of Images as a Story
Zainy M. Malakan, Ghulam Mubashar Hassan, Ajmal Mian
Visual Story-Telling is the process of forming a multi-sentence story from a set of images. Appropriately including visual variation and contextual information captured inside the input images is one of the most challenging aspects of visual storytelling. Consequently, stories developed from a set of images often lack cohesiveness, relevance, and semantic relationship. In this paper, we propose a novel Vision Transformer Based Model for describing a set of images as a story. The proposed method extracts the distinct features of the input images using a Vision Transformer (ViT). Firstly, input images are divided into 16X16 patches and bundled into a linear projection of flattened patches. The transformation from a single image to multiple image patches captures the visual variety of the input visual patterns. These features are used as input to a Bidirectional-LSTM which is part of the sequence encoder. This captures the past and future image context of all image patches. Then, an attention mechanism is implemented and used to increase the discriminatory capacity of the data fed into the language model, i.e. a Mogrifier-LSTM. The performance of our proposed model is evaluated using the Visual Story-Telling dataset (VIST), and the results show that our model outperforms the current state of the art models.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Visual Storytelling | VIST | ViT-model | BLEU-1 | 63 | #25 of 33 | Archive leaderboard | report |
| Visual Storytelling | VIST | ViT-model | BLEU-2 | 37.5 | #25 of 33 | Archive leaderboard | report |
| Visual Storytelling | VIST | ViT-model | BLEU-3 | 21.5 | #25 of 33 | Archive leaderboard | report |
| Visual Storytelling | VIST | ViT-model | BLEU-4 | 12.3 | #25 of 33 | Archive leaderboard | report |
| Visual Storytelling | VIST | ViT-model | CIDEr | 4.4 | #25 of 33 | Archive leaderboard | report |
| Visual Storytelling | VIST | ViT-model | METEOR | 35.4 | #25 of 33 | Archive leaderboard | report |
| Visual Storytelling | VIST | ViT-model | ROUGE-L | 31 | #25 of 33 | 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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