Datasets:
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---
license: cc-by-4.0
task_categories:
- image-classification
- question-answering
- object-detection
tags:
- benchmark
- camera_parameters
- exposure
size_categories:
- 10K<n<100K
language:
- en
configs:
- config_name: default
data_files:
- split: test
path: "data.csv"
---
# SNAP Benchmark
**Code and annotations**: [https://github.com/ykotseruba/SNAP]
**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.
This benchmark allows testing the effects of capture bias, which includes camera settings and illumination, on performance of vision algorithms.
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:
- image classification;
- object detection;
- instance segmentation;
- visual question answering (VQA).
<!-- ## Citation
**BibTeX:** -->
- **Curated by:** Iuliia Kotseruba
- **Shared by:** Iuliia Kotseruba
- **Language(s) (NLP):** English
- **License:** CC-by-4.0 |