# Enhancing Object Detection in Adverse Conditions using Thermal Imaging

Source: [Enhancing Object Detection in Adverse Conditions using Thermal Imaging](<https://www.sota2.com/research/paper/68fa667b1e209131cea107ce>)

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

Data updated: 2025-10-25T21:51:21.649Z

Authors: Kshitij Agrawal, Anbumani Subramanian

Published: 2019-09-30T09:29:48.000Z

## Abstract

Autonomous driving relies on deriving understanding of objects and scenes through images. These images are often captured by sensors in the visible spectrum. For improved detection capabilities we propose the use of thermal sensors to augment the vision capabilities of an autonomous vehicle. In this paper, we present our investigations on the fusion of visible and thermal spectrum images using a publicly available dataset, and use it to analyze the performance of object recognition on other known driving datasets. We present an comparison of object detection in night time imagery and qualitatively demonstrate that thermal images significantly improve detection accuracy.

## 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/1909.13551>)

[PDF](<https://arxiv.org/pdf/1909.13551.pdf>)
