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--- |
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license: cc-by-4.0 |
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task_categories: |
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- image-classification |
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- question-answering |
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- object-detection |
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tags: |
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- benchmark |
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- camera_parameters |
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- exposure |
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size_categories: |
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- 10K<n<100K |
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language: |
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- en |
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configs: |
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- config_name: default |
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data_files: |
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- split: test |
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path: "data.csv" |
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--- |
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# SNAP Benchmark |
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**Code and annotations**: [https://github.com/ykotseruba/SNAP] |
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**SNAP** (stands for **S**hutter speed, **I**SO se**N**sitivity, and **AP**erture) is a new benchmark consisting of images of objects taken under controlled lighting conditions and with densely sampled camera settings. |
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This benchmark allows testing the effects of capture bias, which includes camera settings and illumination, on performance of vision algorithms. |
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SNAP contains **37,558** images of 100 scenes (10 scenes per 10 object categories) uniformly distributed across sensor settings and annotations for the following tasks: |
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- image classification; |
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- object detection; |
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- instance segmentation; |
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- visual question answering (VQA). |
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<!-- ## Citation |
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**BibTeX:** --> |
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- **Curated by:** Iuliia Kotseruba |
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- **Shared by:** Iuliia Kotseruba |
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- **Language(s) (NLP):** English |
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- **License:** CC-by-4.0 |
