research-article

Partially Fake it Till you Make It: Mixing Real and Fake Thermal Images for Improved Object Detection

Authors:

Francesco Bongini,

Lorenzo Berlincioni,

Alberto Del BimboAuthors Info & Claims

MM '21: Proceedings of the 29th ACM International Conference on Multimedia

Pages 5482 - 5490

https://doi.org/10.1145/3474085.3475679

Published: 17 October 2021 Publication History

Abstract

In this paper we propose a novel data augmentation approach for visual content domains that have scarce training datasets, compositing synthetic 3D objects within real scenes. We show the performance of the proposed system in the context of object detection in thermal videos, a domain where i) training datasets are very limited compared to visible spectrum datasets and ii) creating full realistic synthetic scenes is extremely cumbersome and expensive due to the difficulty in modeling the thermal properties of the materials of the scene. We compare different augmentation strategies, including state of the art approaches obtained through RL techniques, the injection of simulated data and the employment of a generative model, and study how to best combine our proposed augmentation with these other techniques. Experimental results demonstrate the effectiveness of our approach, and our single-modality detector achieves state-of-the-art results on the FLIR ADAS dataset.

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Cited By

Zhu GPan HWang QTian CYang CHe ZCai JKankanhalli MPrabhakaran BBoll SSubramanian RZheng LSingh VCesar PXie LXu D(2024)Data Generation Scheme for Thermal Modality with Edge-Guided Adversarial Conditional Diffusion ModelProceedings of the 32nd ACM International Conference on Multimedia10.1145/3664647.3680922(10544-10553)Online publication date: 28-Oct-2024
https://dl.acm.org/doi/10.1145/3664647.3680922
Li SYe MJi LTang SGan YZhu X(2024)Illumination Distribution-Aware Thermal Pedestrian DetectionIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2024.344162825:11(18688-18700)Online publication date: Nov-2024
https://doi.org/10.1109/TITS.2024.3441628
Xie QCheng TDai ZTran VTrigoni NMarkham A(2024)Illumination-Aware Hallucination-Based Domain Adaptation for Thermal Pedestrian DetectionIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2023.330716725:1(315-326)Online publication date: Jan-2024
https://doi.org/10.1109/TITS.2023.3307167
Show More Cited By

Index Terms

Partially Fake it Till you Make It: Mixing Real and Fake Thermal Images for Improved Object Detection
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Object detection
      2. Computer vision representations
        Image representations
  2. Machine learning
    1. Learning settings
      1. Learning from critiques
    2. Machine learning approaches
      1. Neural networks

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cover image ACM Conferences

MM '21: Proceedings of the 29th ACM International Conference on Multimedia

October 2021

5796 pages

ISBN:9781450386517

DOI:10.1145/3474085

General Chairs:
Heng Tao Shen
University of Electronic Science&Technology of China, China
,
Yueting Zhuang
Zhejiang University, China
,
John R. Smith
IBM, USA
,
Program Chairs:
Yang Yang
University of Electronic Science and Technology of China, China
,
Pablo Cesar
CWI&TU Delft, The Netherlands
,
Florian Metze
FACEBOOK, Inc., USA
,
Balakrishnan Prabhakaran
University of Texas at Dallas, USA

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Published: 17 October 2021

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October 20 - 24, 2021

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Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

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Cited By

Zhu GPan HWang QTian CYang CHe ZCai JKankanhalli MPrabhakaran BBoll SSubramanian RZheng LSingh VCesar PXie LXu D(2024)Data Generation Scheme for Thermal Modality with Edge-Guided Adversarial Conditional Diffusion ModelProceedings of the 32nd ACM International Conference on Multimedia10.1145/3664647.3680922(10544-10553)Online publication date: 28-Oct-2024
https://dl.acm.org/doi/10.1145/3664647.3680922
Li SYe MJi LTang SGan YZhu X(2024)Illumination Distribution-Aware Thermal Pedestrian DetectionIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2024.344162825:11(18688-18700)Online publication date: Nov-2024
https://doi.org/10.1109/TITS.2024.3441628
Xie QCheng TDai ZTran VTrigoni NMarkham A(2024)Illumination-Aware Hallucination-Based Domain Adaptation for Thermal Pedestrian DetectionIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2023.330716725:1(315-326)Online publication date: Jan-2024
https://doi.org/10.1109/TITS.2023.3307167
Mayr CKübler CHaala NTeutsch M(2024)Narrowing the Synthetic-to-Real Gap for Thermal Infrared Semantic Image Segmentation Using Diffusion-based Conditional Image Synthesis2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)10.1109/CVPRW63382.2024.00319(3131-3141)Online publication date: 17-Jun-2024
https://doi.org/10.1109/CVPRW63382.2024.00319
Mumuni AMumuni FGerrar N(2024)A Survey of Synthetic Data Augmentation Methods in Machine VisionMachine Intelligence Research10.1007/s11633-022-1411-721:5(831-869)Online publication date: 20-Mar-2024
https://doi.org/10.1007/s11633-022-1411-7
Wei CBai LChen XHan J(2023)Task-Decoupled Knowledge Transfer for Cross-Modality Object DetectionEntropy10.3390/e2508116625:8(1166)Online publication date: 4-Aug-2023
https://doi.org/10.3390/e25081166
Jiang LChen JHuang DWang YEl Saddik AMei TCucchiara RBertini MTobon Vallejo DAtrey PHossain M(2023)MIEP: Channel Pruning with Multi-granular Importance Estimation for Object DetectionProceedings of the 31st ACM International Conference on Multimedia10.1145/3581783.3612563(2908-2917)Online publication date: 26-Oct-2023
https://dl.acm.org/doi/10.1145/3581783.3612563
Madan NSiemon MGjerde MPetersson BGrotuzas AEsbensen MNikolov IPhilipsen MNasrollahi KMoeslund T(2023)ThermalSynth: A Novel Approach for Generating Synthetic Thermal Human Scenarios2023 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW)10.1109/WACVW58289.2023.00018(130-139)Online publication date: Jan-2023
https://doi.org/10.1109/WACVW58289.2023.00018
Farooq MShariff WO’callaghan DMerla ACorcoran P(2023)On the Role of Thermal Imaging in Automotive Applications: A Critical ReviewIEEE Access10.1109/ACCESS.2023.325511011(25152-25173)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3255110
Cauli NReforgiato Recupero D(2022)Survey on Videos Data Augmentation for Deep Learning ModelsFuture Internet10.3390/fi1403009314:3(93)Online publication date: 16-Mar-2022
https://doi.org/10.3390/fi14030093

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