ICCV 2019 Workshop on Real-World Face and Object Recognition from Low-Quality Images and Videos

FOR-LQ 2019


Computer Graphics Computer Vision & Pattern Recognition



The 2nd International Workshop on Real-World Face and Object Recognition from Low-Quality Images and Videos (FOR-LQ)
in conjunction with IEEE ICCV 2019
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What is the current state-of-the-art for recognition and detection algorithms in non-ideal visual environments? Can those algorithms be applied to indeed improving the analysis of realistic surveillance videos? Continuing the success of the 1st FOR-LQ workshop held in the 13th IEEE Conference on Automatic Face and Gesture Recognition (FG 2018), we are organizing its 2nd version in ICCV 2019, with an expanded scope for paper solicitation.
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Call for Papers
[Paper Track]
*Robust facial and object recognition and detection from low-resolution image/video
*Robust facial and object recognition and detection from video with motion blurs
*Robust facial and object recognition and detection from highly noisy image/video
*Robust facial and object recognition and detection from other unconstrained environment conditions
*Low-resolution image/video enhancement, especially for recognition purpose
*Image/video denoising and deblurring, especially for recognition purpose
*Restoration and enhancement of other common degradations, such as low-illumination, inclement weathers, etc., especially for recognition purpose
*Novel methods and metrics for image restoration and enhancement algorithms, especially for recognition purpose
*Surveys of algorithms and applications with LQ inputs in computer vision
*Psychological and cognitive science research with proper data processing and enhancement
*Novel calibration and registration methods on gaze, face or object images for recognition or detection purpose.
*Novel imperfect low-quality data mining, cleaning, and processing methods for training a recognition system.
*Other novel applications that robustly handle computer vision tasks with LQ inputs
[Abstract Track]
We solicit “positioning” writeups, in the form of short non-archival abstracts. They shall address important issues that may generate a lasting impact for next 5-year research in the field of recognition in low-quality visual data. Examples may include but are not limited to,
*Proposing novel technical solutions: preliminary works and “half-baked” results are welcome
*Identifying grand challenges that are traditionally overlooked or under-explored
*Discussing rising applications where recognition from low-quality visual data might have been a critical bottleneck
*Raising new research questions that may be motivated by emerging applications
*New datasets, new benchmark efforts, and/or new evaluation strategies
*Integration of low-quality visual recognition into other research topics
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Authors Guidelines
*Each submitted full-paper must be no longer than eight pages, excluding references. Please refer to the ICCV-2019 author submissions guidelines regarding formatting, templates, and policies. The submissions will go through a double-blind review process by the program committee. Selected papers will be published in ICCV Workshop proceedings.
*Each submitted abstract must be no longer than two pages, excluding references, in the format of ICCV-2019. The non-blind submissions will be also reviewed by the program committee, on a selective and competitive basis. The accepted abstracts will appear on the website. The workshop organizers will lead a collective positioning paper, targeted at a top-tier journal such as TPAMI or IJCV. Those whose abstracts are selected will be invited as co-authors of this paper (the author order will be alphabetical).
*We will set up best paper awards for the full papers.
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Important Dates
Paper submission deadline: Aug. 1, 2019 (11:59PM PST)
Notification to authors: Aug. 20, 2019 (11:59PM PST)
Camera ready deadline: Aug. 30, 2019 (11:59PM PST)
Workshop day: Oct. 27, 2019
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Organization Committee
Yuqian Zhou*, Ph.D Student, UIUC, USA
Yunchao Wei*, Postdoc Researcher & Project Scientist, UIUC, USA
Zhangyang Wang, Assistant Professor, TAMU, USA
Jeffrey Cohn, Professor, Unversity of Pittsburgh and CMU, USA,
Jiaying Liu, Associate Professor, PKU, China
Nicu Sebe, Professor, University of Trento, Italy
Ding Liu, Research Scientist, Bytedance Inc, USA
Honghui Shi, Research Staff Member, IBM Research, USA
Thomas S. Huang, Research Professor, UIUC, USA
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Contact: chairs@forlq.org
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Website: www.forlq.org