CVPR 2026 (Main)
This repository provides the datasets for **“MultiBanana: A Challenging Benchmark for Multi-Reference Text-to-Image Generation” by Yuta Oshima, Daiki Miyake, Kohsei Matsutani, Yusuke Iwasawa, Masahiro Suzuki, Yutaka Matsuo and Hiroki Furuta** ## Paper Link https://arxiv.org/abs/2511.22989 ## Github Repository For the usage of this benchmark, please see Github Repository. https://github.com/matsuolab/multibanana/ ## Dataset Summary MultiBanana-Bench comprises 32 tasks designed to evaluate how well image generation models can faithfully incorporate information from multiple reference images. We report evaluation scores using **Qwen3-VL-8B-Instruct**, a fixed, open-weight judge model. We hope this benchmark, along with its evaluation framework using an open-source VLM as a judge, will serve as a foundation for future research in multi-reference text-to-image generation. ## Acknowledgement This dataset partially incorporates a subset of images from the LAION-5B dataset. We acknowledge and thank the LAION team for making such a valuable large-scale dataset openly available to the research community. ## Opt-out and Removal This dataset contains images from the LAION-5B dataset, which are available on the public internet. If your image represents you or your copyrighted work and you wish to have it removed from this dataset, please contact us at {yuta.oshima, daiki.miyake}[at]g.ecc.u-tokyo.ac.jp with the relevant image. We will remove the entry from the dataset immediately. ## Safety and Ethics While this dataset is derived from LAION, web-crawled data may still contain inappropriate or harmful content. We have applied auto filtering with Gemini-Flash-2.5 and human annotator. Please exercise caution when you viewing the images. ## Citation ``` @inproceedings{oshima2026multibanana, author = {Oshima, Yuta and Miyake, Daiki and Matsutani, Kohsei and Iwasawa, Yusuke and Suzuki, Masahiro and Matsuo, Yutaka and Furuta, Hiroki}, title = {MultiBanana: A Challenging Benchmark for Multi-Reference Text-to-Image Generation}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, month = {June}, year = {2026}, pages = {448-460} } ```