Datasets:

ykotseruba
/

SNAP

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 Shutter speed, ISO seNsitivity, and APerture) 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).

Curated by: Iuliia Kotseruba
Shared by: Iuliia Kotseruba
Language(s) (NLP): English
License: CC-by-4.0