| --- |
| license: mit |
| task_categories: |
| - visual-question-answering |
| language: |
| - en |
| tags: |
| - visual-reasoning |
| - VQA |
| - synthetic |
| - domain-robustness |
| - CLEVR |
| pretty_name: Super-CLEVR |
| size_categories: |
| - 100K<n<1M |
| --- |
| |
| # Super-CLEVR: A Virtual Benchmark to Diagnose Domain Robustness in Visual Reasoning |
|
|
| **[CVPR 2023 Highlight (top 2.5%)]** |
|
|
| Paper: [Super-CLEVR: A Virtual Benchmark to Diagnose Domain Robustness in Visual Reasoning](https://arxiv.org/abs/2212.00259) |
|
|
| **Authors:** Zhuowan Li, Xingrui Wang, Elias Stengel-Eskin, Adam Kortylewski, Wufei Ma, Benjamin Van Durme, Alan Yuille |
|
|
| ## Dataset Description |
|
|
| Super-CLEVR is a synthetic dataset designed to systematically study the **domain robustness** of visual reasoning models across four key factors: |
|
|
| - **Visual complexity** — varying levels of scene and object complexity |
| - **Question redundancy** — controlling redundant information in questions |
| - **Concept distribution** — shifts in the distribution of visual concepts |
| - **Concept compositionality** — novel compositions of known concepts |
|
|
| ## Dataset |
|
|
| Super-CLEVR contains 30k images of vehicles (from [UDA-Part](https://qliu24.github.io/udapart/)) randomly placed in the scenes, with 10 question-answer pairs for each image. The vehicles have part annotations and so the objects in the images can have distinct part attributes. |
|
|
| Here [[link]](https://www.cs.jhu.edu/~zhuowan/zhuowan/SuperCLEVR/obj_part_list/all_objects.html) is the list of objects and parts in Super-CLEVR scenes. |
| |
| The first 20k images and paired are used for training, the next 5k for validation and the last 5k for testing. |
| |
| The dataset is available on [Hugging Face](https://huggingface.co/datasets/RyanWW/Super-CLEVR): |
| |
| | Data | Download Link | |
| |--------------------------|---| |
| | images | [images.zip](https://huggingface.co/datasets/RyanWW/Super-CLEVR/resolve/main/images.zip?download=true) | |
| | scenes | [superCLEVR_scenes.json](https://huggingface.co/datasets/RyanWW/Super-CLEVR/resolve/main/superCLEVR_scenes.json?download=true) | |
| | questions | [superCLEVR_questions_30k.json](https://huggingface.co/datasets/RyanWW/Super-CLEVR/resolve/main/superCLEVR_questions_30k.json?download=true) | |
| | questions (- redundancy) | [superCLEVR_questions_30k_NoRedundant.json](https://huggingface.co/datasets/RyanWW/Super-CLEVR/resolve/main/superCLEVR_questions_30k_NoRedundant.json?download=true) | |
| | questions (+ redundancy) | [superCLEVR_questions_30k_AllRedundant.json](https://huggingface.co/datasets/RyanWW/Super-CLEVR/resolve/main/superCLEVR_questions_30k_AllRedundant.json?download=true) | |
| |
| ## Usage |
| |
| ```python |
| from huggingface_hub import hf_hub_download |
|
|
| # Download a specific file |
| path = hf_hub_download( |
| repo_id="RyanWW/Super-CLEVR", |
| filename="superCLEVR_questions_30k.json", |
| repo_type="dataset", |
| ) |
| ``` |
| |
| ## Citation |
|
|
| ```bibtex |
| @inproceedings{li2023super, |
| title={Super-CLEVR: A Virtual Benchmark to Diagnose Domain Robustness in Visual Reasoning}, |
| author={Li, Zhuowan and Wang, Xingrui and Stengel-Eskin, Elias and Kortylewski, Adam and Ma, Wufei and Van Durme, Benjamin and Yuille, Alan L}, |
| booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition}, |
| pages={14963--14973}, |
| year={2023} |
| } |
| ``` |
|
|
| ## Links |
|
|
| - **Code:** [github.com/Lizw14/Super-CLEVR](https://github.com/Lizw14/Super-CLEVR) |
| - **Paper:** [arxiv.org/abs/2212.00259](https://arxiv.org/abs/2212.00259) |
|
|
| ## License |
|
|
| This dataset is released under the [MIT License](https://opensource.org/licenses/MIT). |
|
|
