# Salient Object Detection for Images Taken by People With Vision Impairments

Source: [Salient Object Detection for Images Taken by People With Vision Impairments](<https://www.sota2.com/research/paper/68fa70821e209131cea4b9d7>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-26T01:44:00.333Z

Authors: Jarek Reynolds, Chandra Kanth Nagesh, Danna Gurari

Published: 2023-01-12T22:33:01.000Z

## Abstract

Salient object detection is the task of producing a binary mask for an image that deciphers which pixels belong to the foreground object versus background. We introduce a new salient object detection dataset using images taken by people who are visually impaired who were seeking to better understand their surroundings, which we call VizWiz-SalientObject. Compared to seven existing datasets, VizWiz-SalientObject is the largest (i.e., 32,000 human-annotated images) and contains unique characteristics including a higher prevalence of text in the salient objects (i.e., in 68\\% of images) and salient objects that occupy a larger ratio of the images (i.e., on average, $\\sim$50\\% coverage). We benchmarked seven modern salient object detection methods on our dataset and found they struggle most with images featuring salient objects that are large, have less complex boundaries, and lack text as well as for lower quality images. We invite the broader community to work on our new dataset challenge by publicly sharing the dataset at https://vizwiz.org/tasks-and-datasets/salient-object .

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2301.05323>)

[PDF](<https://arxiv.org/pdf/2301.05323.pdf>)