ViStoryBench/vistorybench
[CVPR 2026] ViStoryBench: AI Story Visualization Benchmark
This project helps researchers and developers evaluate how well AI models can turn written stories into a sequence of images. You input a written story and the images generated by an AI model, and it produces a detailed assessment of the AI's performance. It is primarily used by AI researchers, machine learning engineers, and computer vision scientists working on generative AI for storytelling.
139 stars.
Use this if you are developing or comparing AI models that generate visual narratives from text and need a standardized way to measure their effectiveness.
Not ideal if you are looking for a tool to generate story visualizations directly, as this focuses solely on evaluating existing generations.
Stars
139
Forks
8
Language
Python
License
Apache-2.0
Category
Last pushed
Mar 04, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/diffusion/ViStoryBench/vistorybench"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
Vchitect/VBench
[CVPR2024 Highlight] VBench - We Evaluate Video Generation
VectorSpaceLab/OmniGen
OmniGen: Unified Image Generation. https://arxiv.org/pdf/2409.11340
EndlessSora/focal-frequency-loss
[ICCV 2021] Focal Frequency Loss for Image Reconstruction and Synthesis
JIA-Lab-research/DreamOmni2
This project is the official implementation of 'DreamOmni2: Multimodal Instruction-based Editing...
SkyworkAI/UniPic
Open-source SOTA multi-image editing model