Browse State-of-the-Art › Story Visualization
Story Visualization
28 papers with code · 3 benchmarks · 1 dataset archive 2025-07-28
Story Visualization is the task of generating coherent and aligned sequence of images given a sequence of textual captions representing description of a story. It mainly consists of two tasks: story generation and story continuation, where story continuation uses additional ground truth information in the form of the first frame.
Description from the archive archive 2025-07-28.
Benchmarks archive 2025-07-28
3 leaderboard tables shown for this task, 3 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.
| Dataset | Best model (first row in archive order) | Paper | Code | Syntology | Compare |
|---|---|---|---|---|---|
| Pororo (5 rows) | ContextualStory | ContextualStory: Consistent Visual Storytelling with... | code | — | Compare |
| CLEVR-SV (1 row) | Impartial Transformer | An Impartial Transformer for Story Visualization | — | — | Compare |
| Zero-Shot Action Execution DiDeMO-CSV (1 row) | Phenaki-Gen | — | — | — | Compare |
Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
1 dataset whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
No subtask under this task in the archive's task tree.
Parent tasks archive 2025-07-28
Most implemented papers archive 2025-07-28
28 shown of 28 papers with code (42 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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16 Oct 2022 2 repositories listed Syntology ran 12 of 21 samples · 9 unverifiedThis task requires machines to 1) understand long text inputs and 2) produce a globally consistent image sequence that illustrates the contents of the story.
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1 Aug 2020 2 repositories listedDifferent from video generation that focuses on maintaining the continuity of generated images (frames), story visualization emphasizes preserving the global consistency of characters and scenes across different story…
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11 Jun 2025 1 repository listedText-to-image generation models have made significant progress in producing high-quality images from textual descriptions, yet they continue to struggle with maintaining subject consistency across multiple images, a…
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30 May 2025 1 repository listed Syntology ran 1 of 2 samples · 1 unverifiedStory visualization, which aims to generate a sequence of visually coherent images aligning with a given narrative and reference images, has seen significant progress with recent advancements in generative models.
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10 Dec 2024 1 repository listedStory visualization has gained increasing attention in artificial intelligence.
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8 Oct 2024 1 repository listed Syntology ran 2 of 7 samples · 5 unverifiedSpecifically, we propose an iterative paradigm to refine each generated image, leveraging both the text prompt and all generated images from the previous iteration.
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13 Jul 2024 1 repository listedVisual storytelling involves generating a sequence of coherent frames from a textual storyline while maintaining consistency in characters and scenes.
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2 Jul 2024 1 repository listed Syntology ran 3 of 4 samples · 1 unverified · 4 pointer-only (licence)Moreover, RCDMs can generate consistent stories with a single forward inference compared to autoregressive models.
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9 Apr 2024 1 repository listed3) The story visualization and continuation models are trained and inferred independently, which is not user-friendly.
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13 Mar 2024 1 repository listedStory Visualization (SV) is a challenging generative vision task, that requires both visual quality and consistency between different frames in generated image sequences.
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5 Feb 2024 1 repository listed Syntology ran 1 of 1 samples · 0 unverifiedText-to-image models offer a new level of creative flexibility by allowing users to guide the image generation process through natural language.
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4 Dec 2023 1 repository listed Syntology ran 9 of 15 samples · 6 unverified · 15 pointer-only (licence)Therefore, we introduce \textbf{StoryGPT-V}, which leverages the merits of the latent diffusion (LDM) and LLM to produce images with consistent and high-quality characters grounded on given story descriptions.
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19 Nov 2023 1 repository listedWe empirically find that sparse control conditions, such as bounding boxes, are suitable for layout planning, while dense control conditions, e.
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16 Nov 2023 1 repository listedRecent advances in text-to-image generation models have unlocked vast potential for visual creativity.
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22 Aug 2023 1 repository listed Syntology ran 14 of 16 samples · 2 unverifiedTo fill this gap, we collect comprehensive human annotations on three existing datasets, and introduce StoryBench: a new, challenging multi-task benchmark to reliably evaluate forthcoming text-to-video models.
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15 Aug 2023 1 repository listedStory visualization (SV) is a challenging text-to-image generation task for the difficulty of not only rendering visual details from the text descriptions but also encoding a long-term context across multiple sentences.
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1 Jun 2023 1 repository listed Syntology ran 0 of 3 samples · 3 unverifiedGenerative models have recently exhibited exceptional capabilities in text-to-image generation, but still struggle to generate image sequences coherently.
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29 May 2023 1 repository listedAccurate Story visualization requires several necessary elements, such as identity consistency across frames, the alignment between plain text and visual content, and a reasonable layout of objects in images.
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23 Nov 2022 1 repository listed Syntology ran 0 of 8 samples · 8 unverifiedOur experiments for story generation on the MUGEN, the PororoSV and the FlintstonesSV dataset show that our method not only outperforms prior state-of-the-art in generating frames with high visual quality, which are…
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20 Nov 2022 1 repository listedConditioned diffusion models have demonstrated state-of-the-art text-to-image synthesis capacity.
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13 Sep 2022 1 repository listed Syntology ran 2 of 3 samples · 1 unverifiedHence, we first propose the task of story continuation, where the generated visual story is conditioned on a source image, allowing for better generalization to narratives with new characters.
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3 Aug 2022 1 repository listed Syntology ran 0 of 1 samples · 1 unverified · 1 pointer-only (licence)Story visualization aims to generate a sequence of images to narrate each sentence in a multi-sentence story with a global consistency across dynamic scenes and characters.
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2 Jun 2022 1 repository listedTo measure the local and global consistency we introduced background and theme awareness, which are expected attributes of the solutions.
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1 Nov 2021 1 repository listedSuch information is even more important for story visualization since its inputs have an explicit narrative structure that needs to be translated into an image sequence (or visual story).
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21 Oct 2021 1 repository listedPrior work in this domain has shown that there is ample room for improvement in the generated image sequence in terms of visual quality, consistency and relevance.
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20 May 2021 1 repository listed Syntology ran 3 of 14 samples · 11 unverifiedTherefore, we also provide an exploration of evaluation metrics for the model, focused on aspects of the generated frames such as the presence/quality of generated characters, the relevance to captions, and the…
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6 Dec 2018 1 repository listedWe therefore propose a new story-to-image-sequence generation model, StoryGAN, based on the sequential conditional GAN framework.
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1 Jun 2018 1 repository listedWe propose an end-to-end network for the visual illustration of a sequence of sentences forming a story.
Syntology lines on 12 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections