mlsanityData to 7 Oct 2026

A Tour of Visualization Techniques for Computer Vision Datasets

arXiv 2204.08601 ↗First posted 19 Apr 2022cs.CV cs.GRcited by 3

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Abstract (arXiv)

We survey a number of data visualization techniques for analyzing Computer Vision (CV) datasets. These techniques help us understand properties and latent patterns in such data, by applying dataset-level analysis. We present various examples of how such analysis helps predict the potential impact of the dataset properties on CV models and informs appropriate mitigation of their shortcomings. Finally, we explore avenues for further visualization techniques of different modalities of CV datasets as well as ones that are tailored to support specific CV tasks and analysis needs.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 24 of its 63 references that are in the map. First posted on arXiv 19 Apr 2022.

Builds on

24 of 63 references.

References · 24

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12 more
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Citing papers per year: 2023: 3.

3 papers.

  1. 2023Spatial encoding of BOLD fMRI time series for categorizing static images across visual datasets: A pilot study on human visioncited by 6
  2. 2023Image complexity based fMRI-BOLD visual network categorization across visual datasets using topological descriptors and deep-hybrid learningcited by 5
  3. 2023Investigating the changes in BOLD responses during viewing of images with varied complexity: An fMRI time-series based analysis on human visioncited by 2