# Evaluation of Object Detection Proposals Under Condition Variations

Source: [Evaluation of Object Detection Proposals Under Condition Variations](<https://www.sota2.com/research/paper/68fa62331e209131ce9f8336>)

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

Data updated: 2025-10-27T05:50:53.386Z

Authors: Fahimeh Rezazadegan, Sareh Shirazi, Michael Milford, Ben Upcroft

Published: 2015-12-10T06:31:59.000Z

## Abstract

Object detection is a fundamental task in many computer vision applications, therefore the importance of evaluating the quality of object detection is well acknowledged in this domain. This process gives insight into the capabilities of methods in handling environmental changes. In this paper, a new method for object detection is introduced that combines the Selective Search and EdgeBoxes. We tested these three methods under environmental variations. Our experiments demonstrate the outperformance of the combination method under illumination and view point variations.

## 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/1512.03424>)

[PDF](<https://arxiv.org/pdf/1512.03424.pdf>)