metadata

license: cc-by-nc-4.0
task_categories:
  - visual-question-answering
language:
  - en
pretty_name: SEED-Bench-2
size_categories:
  - 10K<n<100K

SEED-Bench Card

Benchmark details

Benchmark type: SEED-Bench-2 is a comprehensive large-scale benchmark for evaluating Multimodal Large Language Models (MLLMs), featuring 24K multiple-choice questions with precise human annotations. It spans 27 evaluation dimensions, assessing both text and image generation.

Benchmark date: SEED-Bench was collected in November 2023.

Paper or resources for more information: https://github.com/AILab-CVC/SEED-Bench

License: Attribution-NonCommercial 4.0 International. It should abide by the policy of OpenAI: https://openai.com/policies/terms-of-use.

Data Sources:

Dimensions 1-9, 23 (In-Context Captioning): Conceptual Captions Dataset (https://ai.google.com/research/ConceptualCaptions/) under its license (https://github.com/google-research-datasets/conceptual-captions/blob/master/LICENSE). Copyright belongs to the original dataset owner.
Dimension 9 (Text Recognition): ICDAR2003 (http://www.imglab.org/db/index.html), ICDAR2013(https://rrc.cvc.uab.es/?ch=2), IIIT5k(https://cvit.iiit.ac.in/research/projects/cvit-projects/the-iiit-5k-word-dataset), and SVT(http://vision.ucsd.edu/~kai/svt/). Copyright belongs to the original dataset owner.
Dimension 10 (Celebrity Recognition): MME (https://github.com/BradyFU/Awesome-Multimodal-Large-Language-Models/tree/Evaluation) and MMBench (https://github.com/open-compass/MMBench) under MMBench license (https://github.com/open-compass/MMBench/blob/main/LICENSE). Copyright belongs to the original dataset owners.
Dimension 11 (Landmark Recognition): Google Landmark Dataset v2 (https://github.com/cvdfoundation/google-landmark) under CC-BY licenses without ND restrictions.
Dimension 12 (Chart Understanding): PlotQA (https://github.com/NiteshMethani/PlotQA) under its license (https://github.com/NiteshMethani/PlotQA/blob/master/LICENSE).
Dimension 13 (Visual Referring Expression): VCR (http://visualcommonsense.com) under its license (http://visualcommonsense.com/license/).
Dimension 14 (Science Knowledge): ScienceQA (https://github.com/lupantech/ScienceQA) under its license (https://github.com/lupantech/ScienceQA/blob/main/LICENSE-DATA).
Dimension 15 (Emotion Recognition): FER2013 (https://www.kaggle.com/competitions/challenges-in-representation-learning-facial-expression-recognition-challenge/data) under its license (https://www.kaggle.com/competitions/challenges-in-representation-learning-facial-expression-recognition-challenge/rules#7-competition-data).
Dimension 16 (Visual Mathematics): MME (https://github.com/BradyFU/Awesome-Multimodal-Large-Language-Models/tree/Evaluation) and data from the internet under CC-BY licenses.
Dimension 17 (Difference Spotting): MIMICIT (https://github.com/Luodian/Otter/blob/main/mimic-it/README.md) under its license (https://github.com/Luodian/Otter/tree/main/mimic-it#eggs).
Dimension 18 (Meme Comprehension): Data from the internet under CC-BY licenses.
Dimension 19 (Global Video Understanding): Charades (https://prior.allenai.org/projects/charades) under its license (https://prior.allenai.org/projects/data/charades/license.txt). SEED-Bench-2 provides 8 frames per video.
Dimensions 20-22 (Action Recognition, Action Prediction, Procedure Understanding): Something-Something v2 (https://developer.qualcomm.com/software/ai-datasets/something-something), Epic-Kitchen 100 (https://epic-kitchens.github.io/2023), and Breakfast (https://serre-lab.clps.brown.edu/resource/breakfast-actions-dataset/). SEED-Bench-2 provides 8 frames per video.
Dimension 24 (Interleaved Image-Text Analysis): Data from the internet under CC-BY licenses.
Dimension 25 (Text-to-Image Generation): CC-500 (https://github.com/weixi-feng/Structured-Diffusion-Guidance) and ABC-6k (https://github.com/weixi-feng/Structured-Diffusion-Guidance) under their license (https://github.com/weixi-feng/Structured-Diffusion-Guidance/blob/master/LICENSE), with images generated by Stable-Diffusion-XL (https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0) under its license (https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/blob/main/LICENSE.md).
Dimension 26 (Next Image Prediction): Epic-Kitchen 100 (https://epic-kitchens.github.io/2023) under its license (https://creativecommons.org/licenses/by-nc/4.0/).
Dimension 27 (Text-Image Creation): Data from the internet under CC-BY licenses.

Please contact us if you believe any data infringes upon your rights, and we will remove it.

Where to send questions or comments about the benchmark: https://github.com/AILab-CVC/SEED-Bench/issues

Intended use

Primary intended uses: SEED-Bench-2 is primarily designed to evaluate Multimodal Large Language Models in text and image generation tasks.

Primary intended users: Researchers and enthusiasts in computer vision, natural language processing, machine learning, and artificial intelligence are the main target users of the benchmark.