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Low-light Pedestrian Detection in Visible and Infrared Image Feeds: Issues and Challenges

arXiv 2311.08557 ↗First posted 14 Nov 2023cs.CV cs.AI cs.LGcited by 0

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Abstract (arXiv)

Pedestrian detection has become a cornerstone for several high-level tasks, including autonomous driving, intelligent transportation, and traffic surveillance. There are several works focussed on pedestrian detection using visible images, mainly in the daytime. However, this task is very intriguing when the environmental conditions change to poor lighting or nighttime. Recently, new ideas have been spurred to use alternative sources, such as Far InfraRed (FIR) temperature sensor feeds for detecting pedestrians in low-light conditions. This study reviews recent developments in low-light pedestrian detection approaches. It systematically categorizes and analyses various algorithms from region-based to non-region-based and graph-based learning methodologies by highlighting their methodologies, implementation issues, and challenges. It also outlines the key benchmark datasets that can be used for research and development of advanced pedestrian detection algorithms, particularly in low-light situations.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 34 of its 94 references that are in the map. First posted on arXiv 14 Nov 2023.

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34 of 94 references.

References · 34

  1. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  2. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,267
  3. 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,617
  4. 2017Graph Attention Networkscited by 8,854
  5. 2015You Only Look Once: Unified, Real-Time Object Detectioncited by 4,829
  6. 2018How Powerful are Graph Neural Networks?cited by 4,355
  7. 2015SSD: Single Shot MultiBox Detectorcited by 3,125
  8. 2015Fast R-CNNcited by 2,930
  9. 2016Pyramid Scene Parsing Networkcited by 2,472
  10. 2013Rich feature hierarchies for accurate object detection and semantic segmentationcited by 2,160
  11. 2017Unsupervised Image-to-Image Translation Networkscited by 602
  12. 2017Scene Graph Generation by Iterative Message Passingcited by 462
22 more
  1. 2020Point-GNN: Graph Neural Network for 3D Object Detection in a Point Cloudcited by 335
  2. 2020Towards Deeper Graph Neural Networkscited by 296
  3. 2021LLVIP: A Visible-infrared Paired Dataset for Low-light Visioncited by 229
  4. 2013OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networkscited by 224
  5. 2018Getting to Know Low-light Images with The Exclusively Dark Datasetcited by 157
  6. 2016Multispectral Deep Neural Networks for Pedestrian Detectioncited by 82
  7. 2018Illumination-aware Faster R-CNN for Robust Multispectral Pedestrian Detectioncited by 74
  8. 2016T-CNN: Tubelets with Convolutional Neural Networks for Object Detection from Videoscited by 67
  9. 2022Adaptive Trajectory Prediction via Transferable GNNcited by 51
  10. 2017MSR-net:Low-light Image Enhancement Using Deep Convolutional Networkcited by 43
  11. 2019Borrow from Anywhere: Pseudo Multi-modal Object Detection in Thermal Imagerycited by 38
  12. 2020Cascade Graph Neural Networks for RGB-D Salient Object Detectioncited by 36
  13. 2020From Handcrafted to Deep Features for Pedestrian Detection: A Surveycited by 30
  14. 2017Illuminating Pedestrians via Simultaneous Detection & Segmentationcited by 26
  15. 2019FuseMODNet: Real-Time Camera and LiDAR based Moving Object Detection for robust low-light Autonomous Drivingcited by 26
  16. 2021GraphFPN: Graph Feature Pyramid Network for Object Detectioncited by 25
  17. 2021Graph and Recurrent Neural Network-based Vehicle Trajectory Prediction For Highway Drivingcited by 19
  18. 2019Pedestrian Detection in Thermal Images using Saliency Mapscited by 15
  19. 2016Fused DNN: A deep neural network fusion approach to fast and robust pedestrian detectioncited by 10
  20. 2019Semantic Head Enhanced Pedestrian Detection in a Crowdcited by 8
  21. 2021Exploring Low-light Object Detection Techniquescited by 5
  22. 2018Infrared and visible image fusion using Latent Low-Rank Representationcited by 4

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