license: apache-2.0
task_categories:
- question-answering
- multiple-choice
- visual-question-answering
language:
- en
tags:
- music
pretty_name: AV_Odyssey
size_categories:
- 1K<n<10K
dataset_info:
features:
- name: question_id
dtype: string
- name: question_type_id
dtype: string
- name: data_type
dtype: string
- name: subfield
dtype: string
- name: question
dtype: string
- name: options
sequence: string
- name: answer
dtype: string
- name: image_1
dtype: image
- name: image_2
dtype: image
- name: image_3
dtype: image
- name: image_4
dtype: image
- name: video_1
dtype: string
- name: audio_1
dtype: audio
- name: audio_2
dtype: audio
- name: audio_3
dtype: audio
- name: audio_4
dtype: audio
splits:
- name: test
num_bytes: 2722106.18
num_examples: 400
download_size: 2715938
dataset_size: 2722106.18
configs:
- config_name: default
data_files:
- split: test
path: av_odyssey_part*
Official dataset for the paper "AV-Odyssey: Can Your Multimodal LLMs Really Understand Audio-Visual Information?".
🌟 For more details, please refer to the project page with data examples: https://av-odyssey.github.io/.
[🌐 Webpage] [📖 Paper] [🤗 Huggingface AV-Odyssey Dataset] [🤗 Huggingface Deaftest Dataset] [🏆 Leaderboard]
🔥 News
2024.11.24🌟 We release AV-Odyssey, the first-ever comprehensive evaluation benchmark to explore whether MLLMs really understand audio-visual information.
👀 About AV-Odyssey
Recently, multimodal large language models (MLLMs), such as GPT-4o, Gemini 1.5 Pro, and Reka Core, have expanded their capabilities to include vision and audio modalities. While these models demonstrate impressive performance across a wide range of audio-visual applications, our proposed DeafTest reveals that MLLMs often struggle with simple tasks humans find trivial: 1) determining which of two sounds is louder, and 2) determining which of two sounds has a higher pitch. Motivated by these observations, we introduce AV-Odyssey Bench. This benchmark encompasses 26 different tasks and 4,555 carefully crafted problems, each incorporating text, visual, and audio components. All data are newly collected and annotated by humans, not from any existing audio-visual dataset. AV-Odyssey Bench demonstrates three major features: 1. Comprehensive Audio Attributes; 2. Extensive Domains; 3. Interleaved Text, Audio, and Visual components.
📐 Data Examples
Please refer to our project page https://av-odyssey.github.io/ for exploring more examples.
📍AV-Odyssey Bench
🔍 Dataset
License:
AV-Odyssey is only used for academic research. Commercial use in any form is prohibited.
The copyright of all videos belongs to the video owners.
If there is any infringement in AV-Odyssey, please email libohao1998@gmail.com and we will remove it immediately.
Without prior approval, you cannot distribute, publish, copy, disseminate, or modify AV-Odyssey in whole or in part.
You must strictly comply with the above restrictions.
Please send an email to libohao1998@gmail.com. 🌟
🔮 Evaluation Pipeline
🏆 Leaderboard
Contributing to the AV-Odyssey Leaderboard
🚨 The Leaderboard for AV-Odyssey is continuously being updated, welcoming the contribution of your excellent MLLMs!