StoryDiffusion: consistent self-attention for long-range image and video generation
Source: https://github.com/hvision-nku/storydiffusion
Structured fields
{
"archived": false,
"checked_at": "2026-10-17T00:00:00.000Z",
"usefulness": "Training-free consistent self-attention giving character-consistent image sequences (comic/storyboard panels) and a motion-prediction step for longer video; official code with a comic-generation demo.",
"source_type": "repository",
"availability": "available",
"source_owner": "HVision-NKU (Nankai University)",
"next_check_at": "2026-11-16T00:00:00.000Z",
"hardware_notes": "Not checked.",
"known_limitations": [
"Character consistency is for prompts within one batch; behaviour on current base models not verified."
],
"upstream_updated_at": "2024-09-26T02:17:52.000Z"
}Evidence claims
- [sourced_fact] README: StoryDiffusion, Consistent Self-Attention for Long-Range Image and Video Generation (NeurIPS 2024 Spotlight); links paper, project page, Jittor version and comic demo. · locator: README header source
- [upstream_claim] Paper abstract: Consistent Self-Attention boosts consistency across generated images in a zero-shot manner with pretrained text-to-image models. · locator: abstract source
- [sourced_fact] Repository LICENSE is Apache-2.0; last push 2024-09-26. · locator: LICENSE file source
- [upstream_claim] Research review verdict at export: reviewed (as of 2026-10-17). Recorded by the research pipeline, not a hub review outcome; evidence.review stays unreviewed until an independent reviewer records one.
Rights
| component | license | hosting | redistribution | modification | training | Evidence and notes |
|---|---|---|---|---|---|---|
| code | Apache-2.0 | permitted | permitted | permitted | unknown | Apache-2.0 for repository code. Base diffusion model licenses and any weights are separate and were not checked. |
| documentation | CC-BY-NC-SA-4.0 | restricted | restricted | restricted | unknown | arXiv page lists CC BY-NC-SA 4.0 for the paper. |