Workshop on
Multispectral Imaging for Robotics and Automation
(MIRA)

co-located with ACCV 2024 and ACML 2024

Hanoi, Vietnam - December 8th, 2024



Introduction

Multispectral imaging is revolutionizing the fields of robotics and automation by providing richer information beyond the visible spectrum. Traditional RGB cameras capture only a narrow band of the electromagnetic spectrum, limiting the data available for computer vision systems. Multispectral cameras expand this capability by sensing light across a broader range of wavelengths, including infrared, ultraviolet, and other portions of the spectrum invisible to the human eye.

This additional spectral information unlocks powerful new applications in robotics and automation. Multispectral data can be used for enhanced material classification, detecting various objects, identifying chemical signatures, and perceiving environmental factors like moisture and temperature. Additionally, in autonomous driving, multispectral imaging allows vehicles to detect lane markings better, read traffic signals, and identify obstacles in challenging conditions like adverse weather situations and darkness. Such capabilities have transformative potential for industrial inspection, agricultural automation, search and rescue operations, self-driving cars, and countless other domains.

The Multispectral Imaging for Robotics and Automation (MIRA) workshop aims to bring together leading researchers exploring this emerging interdisciplinary area at the intersection of multispectral imaging, computer vision, robotics, and automation.

Join us to discuss the latest breakthroughs, share cutting-edge research, and forge new collaborations driving innovation in this exciting field.


Call For Papers

We invite researchers and practitioners to submit original and unpublished work to the Multispectral Imaging for Robotics and Automation (MIRA) workshop. Relevant topics include but are not limited to:

  • Multispectral image acquisition and sensor fusion
  • Multispectral object detection, tracking, and segmentation
  • Industrial inspection with multispectral vision
  • Agricultural monitoring and automation
  • Non-line-of-sight imaging for autonomous vehicles
  • Multispectral perception for adverse weather conditions
  • Novel applications of multispectral data in robotics and automation
  • Multispectral image reconstruction
  • Spectral unmixing and material classification
  • Domain adaptation and transfer learning for multispectral data
  • Multispectral dataset curation and benchmarking

Paper Submission Guidelines:
To submit papers for consideration, please utilize the workshop's CMT website: https://cmt3.research.microsoft.com/MIRA2024. All submissions should be in PDF format.
Papers that have been previously published or are currently under review elsewhere will not be accepted. It is imperative that submissions adhere to the formatting standards outlined by the Asian Conference on Computer Vision (ACCV), which can be found at https://accv2024.org/author-guidelines/.
For consistency, papers must use the ACCV LaTeX template and should not exceed 14 pages, including figures and tables. However, additional pages are permissible solely for references.
You can access the official ACCV LaTeX template files by cloning the template from this overleaf project or downloading this zip file.
All accepted papers are going to be published in the ACCV 2024 Workshop proceedings and Springer ACCV 2024 Workshop LNCS.
Important note: PDF files must be under 20MB.


Important Dates

Call for papers announced July 9, 2024
Paper submission deadline September 14, 2024
Notifications to accepted papers September 20, 2024
Paper camera ready September 30, 2024
Workshop date December 8, 2024


Invited Speakers

Kailun Yang (Hunan University (HNU)) Kailun Yang is a Professor at the School of Robotics and the National Engineering Research Center of Robot Visual Perception and Control Technology at Hunan University. He earned his PhD in Information Sensing and Instrumentation from Zhejiang University, where he was jointly supervised by experts from Zhejiang University and the University of Alcalá. Prior to his PhD, he completed dual B.S. degrees in Measurement Technology and Instrumentation from Beijing Institute of Technology and Economics from Peking University. His postdoctoral research at the CV Lab, Karlsruhe Institute of Technology, focused on human-computer interaction under the guidance of Prof. Rainer Stiefelhagen. Kailun Yang’s research spans multimodal, high-dimensional, and full-view computational optics and vision, with applications in autonomous driving, blind assistance, intelligent transportation systems, and motion analysis. He has made countless contributions to the field of multispectral imaging, with notable works such as ACNet: Attention Based Network to Exploit Complementary Features for RGBD Semantic Segmentation, CMX: Cross-Modal Fusion for RGB-X Semantic Segmentation with Transformers, and CFMW: Cross-Modality Fusion Mamba for Multispectral Object Detection under Adverse Weather Conditions.


Rui Fan (Tongji University) Rui Fan received the B.Eng. degree in Automation from the Harbin Institute of Technology in 2015 and the Ph.D. degree in Electrical and Electronic Engineering from the University of Bristol in 2018. He worked as a Research Associate at the Hong Kong University of Science and Technology from 2018 to 2020 and a Postdoctoral Scholar-Employee at the University of California San Diego between 2020 and 2021. He began his faculty career as a Full Research Professor with the College of Electronics & Information Engineering at Tongji University in 2021, and was then promoted to a Full Professor in the same college, as well as at the Shanghai Research Institute for Intelligent Autonomous Systems in 2022. Prof. Fan served as an associate editor for ICRA'23/25 and IROS'23/24, an area chair for ICIP'24, and a senior program committee member for AAAI'23/24/25. He is the general chair of the AVVision community and organized several impactful workshops and special sessions in conjunction with WACV'21, ICIP'21/22/23, ICCV'21, and ECCV'22. He was honored by being included in the Stanford University List of Top 2% Scientists Worldwide between 2022 and 2024, recognized on the Forbes China List of 100 Outstanding Overseas Returnees in 2023, and acknowledged as one of Xiaomi Young Talents in 2023. His research interests include computer vision, deep learning, and robotics, with a specific focus on humanoid visual perception under the two-streams hypothesis.


Ukcheol Shin (Carnegie Mellon University) Ukcheol Shin is a postdoctoral researcher at the Robotics Institute of Carnegie Mellon University. His research focuses on developing a robust robot vision system that can perceive and navigate the dynamic world, even in challenging conditions, with a particular interest in self-supervised learning of 3D geometry and multi-sensor fusion. Dr. Shin has made significant contributions to the field of multispectral imaging, with a focus on topics such as thermal image segmentation and depth estimation on thermal images. Furthermore, he is one of the authors of the MS2 dataset, a valuable resource for the research community.


Ashutosh Mishra (BITS Pilani) Ashutosh Mishra is an academic and researcher specializing in Intelligent Systems. He holds a B.Tech. from Uttar Pradesh Technical University (2008), an M.Tech. from NIT Allahabad (2011), and a Ph.D. from IIT (BHU) Varanasi (2018). He was an Assistant Professor at NIT Raipur and received the Korea Research Fellowship in 2019. From 2019 to 2023, he was a Brain Pool Fellow at Yonsei University, South Korea. Currently, he is an Assistant Professor in the Department of Electrical & Electronics Engineering at BITS Pilani, Dubai. His research interests include smart sensors, intelligent systems, autonomous vehicles, convergence technology, and artificial intelligence.


Schedule (Hanoi, Vietnam / Indochina Time Zone (ICT) (*GMT +7))

Will be announced soon.


Organizers

  • Dr. Yağız Nalçakan - Seamless Trans-X Lab - Yonsei University
  • Yeongwan Jin - Seamless Trans-X Lab - Yonsei University
  • Hyeongjin Ju - Seamless Trans-X Lab - Yonsei University
  • Hanbin Song - Seamless Trans-X Lab - Yonsei University
  • Incheol Park - Seamless Trans-X Lab - Yonsei University

  • Program Committee

  • Prof. Shiho Kim (program chair) - Yonsei University
  • Prof. Guofa Li - Chongqing University
  • Prof. Chih-Hsien Hsia - National Ilan University
  • Dr. Ashutosh Mishra - Birla Institute of Technology and Science
  • Dr. Jianwu Fang - Chang'an University
  • Dr. Jifeng Shen - Jiangsu University
  • Dr. Di Yuan - Xidian University

  • Contact

    To contact the organizers please use multispectral4ra@outlook.com



    Acknowledgments

    Thanks to visualdialog.org and L3DS workshop team for the webpage format.